ADNI enrollment summaries using the ADNIMERGE R package

Description

This package vignette demonstrates how to use the ADNIMERGE package to generate simple enrollment and longitudinal summaries and plots with R and knitr.

Report generated from Enrollment.Rmd

Load required R packages and functions

options(digits = 3)
library(knitr)
library(ADNIMERGE)
library(ggplot2)
library(Hmisc)
library(gridExtra)
library(RColorBrewer)
source("https://adni.bitbucket.io/myfunctions.R")
theme_set(theme_bw())

dd <- adnimerge
dd$AGEC <- cut(dd$AGE, breaks = seq(39, 110, by = 10))

label(dd$PTEDUCAT) <- "Education"
label(dd$AGE) <- "Age"
label(dd$AGEC) <- "Age"
label(dd$PTGENDER) <- "Sex"
label(dd$PTETHCAT) <- "Ethnicity"
label(dd$PTRACCAT) <- "Race"
label(dd$PTMARRY) <- "Marital"
label(dd$CDRSB) <- "CDR-SB"
label(dd$ADAS11) <- "ADAS 11"
label(dd$ADAS13) <- "ADAS 13"
label(dd$MMSE) <- "MMSE"

# indicate the bl withdrawals:
BLTDS <- subset(treatdis, VISCODE == "bl" & WDRAWTYPE == "Full")$RID
dd$VISCODE <- with(dd, ifelse(VISCODE == "bl" & RID %in% BLTDS, "blwd", VISCODE))

Demographic Summaries by Diagnosis

Baseline

# Subsetting on RID < 2000 excludes ADNIGO/2 subjects
summary(DX.bl ~ AGE + AGEC + PTGENDER + PTEDUCAT + PTMARRY + PTETHCAT + PTRACCAT + 
    CDRSB + ADAS13 + MMSE, data = dd, subset = VISCODE %in% c("bl", "blwd"), method = "reverse", 
    test = TRUE, overall = TRUE)

Descriptive Statistics by Baseline Dx

	N	CN (N=523)	SMC (N=304)	EMCI (N=404)	LMCI (N=661)	AD (N=400)	Combined (N=2292)	Test Statistic
Age [Years]	2302	`69.9/73.2/77.7`	`66.8/70.2/75.7`	`66.0/71.5/76.4`	`69.2/74.3/79.2`	`70.5/75.3/80.3`	`68.2/73.2/78.3`	F=21.7 d.f.=4,2283 P<0.001
Age : (39,49]	2301	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	Chi-square=164 d.f.=16 P<0.001
(49,59]		`1% ( 6)`	`2% ( 6)`	`4% ( 17)`	`3% ( 21)`	`4% ( 16)`	`3% ( 66)`
(59,69]		`19% ( 101)`	`41% ( 126)`	`35% ( 143)`	`21% ( 138)`	`16% ( 66)`	`25% ( 574)`
(69,79]		`61% ( 319)`	`45% ( 137)`	`44% ( 178)`	`49% ( 325)`	`47% ( 187)`	`50% (1146)`
(79,89]		`18% ( 95)`	`10% ( 31)`	`16% ( 64)`	`26% ( 172)`	`31% ( 124)`	`21% ( 486)`
(89,99]		`0% ( 1)`	`1% ( 4)`	`0% ( 1)`	`0% ( 3)`	`2% ( 7)`	`1% ( 16)`
(99,109]		`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`
Sex : Male	2306	`47% ( 247)`	`38% ( 116)`	`56% ( 226)`	`62% ( 407)`	`56% ( 226)`	`53% (1222)`	Chi-square=56.7 d.f.=4 P<0.001
Education	2306	`14/16/18`	`16/17/18`	`14/16/18`	`14/16/18`	`13/16/18`	`14/16/18`	F=15.6 d.f.=4,2287 P<0.001
Marital : Divorced	2306	`11% ( 55)`	`13% ( 39)`	`11% ( 44)`	`8% ( 53)`	`4% ( 14)`	`9% ( 205)`	Chi-square=66.9 d.f.=16 P<0.001
Married		`69% ( 360)`	`72% ( 218)`	`78% ( 314)`	`78% ( 516)`	`84% ( 338)`	`76% (1746)`
Never married		`6% ( 29)`	`5% ( 15)`	`4% ( 16)`	`2% ( 13)`	`2% ( 10)`	`4% ( 83)`
Unknown		`0% ( 1)`	`0% ( 1)`	`1% ( 4)`	`0% ( 2)`	`0% ( 0)`	`0% ( 8)`
Widowed		`15% ( 78)`	`10% ( 31)`	`6% ( 26)`	`12% ( 77)`	`10% ( 38)`	`11% ( 250)`
Ethnicity : Unknown	2306	`0% ( 2)`	`1% ( 2)`	`0% ( 2)`	`0% ( 3)`	`1% ( 3)`	`1% ( 12)`	Chi-square=5.71 d.f.=8 P=0.68
Not Hisp/Latino		`95% ( 498)`	`95% ( 289)`	`94% ( 380)`	`97% ( 639)`	`96% ( 383)`	`96% (2189)`
Hisp/Latino		`4% ( 23)`	`4% ( 13)`	`5% ( 22)`	`3% ( 19)`	`4% ( 14)`	`4% ( 91)`
Race : Am Indian/Alaskan	2306	`0% ( 2)`	`0% ( 0)`	`0% ( 2)`	`0% ( 1)`	`0% ( 0)`	`0% ( 5)`	Chi-square=54.6 d.f.=24 P<0.001
Asian		`2% ( 9)`	`3% ( 10)`	`1% ( 5)`	`2% ( 12)`	`2% ( 10)`	`2% ( 46)`
Hawaiian/Other PI		`0% ( 0)`	`0% ( 0)`	`0% ( 1)`	`0% ( 1)`	`0% ( 0)`	`0% ( 2)`
Black		`7% ( 36)`	`8% ( 23)`	`3% ( 11)`	`5% ( 30)`	`4% ( 18)`	`5% ( 118)`
White		`91% ( 474)`	`86% ( 260)`	`92% ( 373)`	`93% ( 613)`	`92% ( 368)`	`91% (2088)`
More than one		`0% ( 2)`	`3% ( 10)`	`2% ( 8)`	`0% ( 3)`	`1% ( 4)`	`1% ( 27)`
Unknown		`0% ( 0)`	`0% ( 1)`	`1% ( 4)`	`0% ( 1)`	`0% ( 0)`	`0% ( 6)`
CDR-SB	2306	`0.00/0.00/0.00`	`0.00/0.00/0.00`	`0.50/1.00/1.62`	`1.00/1.50/2.00`	`3.50/4.50/5.12`	`0.00/1.00/2.50`	F=2921 d.f.=4,2287 P<0.001
ADAS 13	2282	`6.83/ 9.67/13.00`	`8.33/11.00/14.33`	`9.00/14.00/17.00`	`14.67/18.67/23.33`	`24.67/29.67/35.00`	`10.00/15.00/22.59`	F=667 d.f.=4,2266 P<0.001
MMSE	2306	`29/29/30`	`29/29/30`	`28/29/29`	`26/27/29`	`21/23/25`	`26/28/29`	F=602 d.f.=4,2287 P<0.001

Demographic Summaries by Diagnosis

Baseline

# Subsetting on RID > 2000 excludes ADNI1 subjects
summary(DX.bl ~ AGE + AGEC + PTGENDER + PTEDUCAT + PTMARRY + PTETHCAT + PTRACCAT + 
    CDRSB + ADAS13 + MMSE, data = dd, subset = VISCODE == "bl", method = "reverse", 
    test = TRUE, overall = TRUE)

Descriptive Statistics by Baseline Dx

	N	CN (N=516)	SMC (N=301)	EMCI (N=393)	LMCI (N=649)	AD (N=390)	Combined (N=2249)	Test Statistic
Age [Years]	2259	`69.9/73.2/77.7`	`66.8/70.2/75.8`	`66.2/71.5/76.4`	`69.2/74.3/79.2`	`70.5/75.3/80.3`	`68.2/73.2/78.2`	F=20.8 d.f.=4,2240 P<0.001
Age : (39,49]	2258	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	Chi-square=159 d.f.=16 P<0.001
(49,59]		`1% ( 6)`	`2% ( 6)`	`4% ( 16)`	`3% ( 20)`	`4% ( 16)`	`3% ( 64)`
(59,69]		`19% ( 99)`	`42% ( 125)`	`35% ( 138)`	`21% ( 136)`	`16% ( 64)`	`25% ( 562)`
(69,79]		`61% ( 315)`	`45% ( 135)`	`45% ( 175)`	`49% ( 320)`	`47% ( 183)`	`50% (1128)`
(79,89]		`18% ( 94)`	`10% ( 31)`	`16% ( 62)`	`26% ( 168)`	`31% ( 120)`	`21% ( 475)`
(89,99]		`0% ( 1)`	`1% ( 4)`	`0% ( 1)`	`0% ( 3)`	`2% ( 7)`	`1% ( 16)`
(99,109]		`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`
Sex : Male	2263	`47% ( 245)`	`38% ( 114)`	`56% ( 222)`	`62% ( 401)`	`57% ( 221)`	`53% (1203)`	Chi-square=58 d.f.=4 P<0.001
Education	2263	`14/16/18`	`16/17/18`	`14/16/18`	`14/16/18`	`13/16/18`	`14/16/18`	F=15.1 d.f.=4,2244 P<0.001
Marital : Divorced	2263	`10% ( 54)`	`13% ( 39)`	`11% ( 42)`	`8% ( 53)`	`4% ( 14)`	`9% ( 202)`	Chi-square=65.7 d.f.=16 P<0.001
Married		`69% ( 357)`	`72% ( 217)`	`78% ( 308)`	`78% ( 506)`	`84% ( 329)`	`76% (1717)`
Never married		`5% ( 28)`	`5% ( 15)`	`4% ( 15)`	`2% ( 12)`	`3% ( 10)`	`4% ( 80)`
Unknown		`0% ( 1)`	`0% ( 1)`	`1% ( 4)`	`0% ( 2)`	`0% ( 0)`	`0% ( 8)`
Widowed		`15% ( 76)`	`10% ( 29)`	`6% ( 24)`	`12% ( 76)`	`9% ( 37)`	`11% ( 242)`
Ethnicity : Unknown	2263	`0% ( 2)`	`1% ( 2)`	`1% ( 2)`	`0% ( 3)`	`1% ( 3)`	`1% ( 12)`	Chi-square=6.04 d.f.=8 P=0.643
Not Hisp/Latino		`95% ( 491)`	`95% ( 286)`	`94% ( 370)`	`97% ( 628)`	`96% ( 374)`	`96% (2149)`
Hisp/Latino		`4% ( 23)`	`4% ( 13)`	`5% ( 21)`	`3% ( 18)`	`3% ( 13)`	`4% ( 88)`
Race : Am Indian/Alaskan	2263	`0% ( 2)`	`0% ( 0)`	`1% ( 2)`	`0% ( 1)`	`0% ( 0)`	`0% ( 5)`	Chi-square=55.1 d.f.=24 P<0.001
Asian		`2% ( 9)`	`3% ( 10)`	`1% ( 5)`	`2% ( 12)`	`3% ( 10)`	`2% ( 46)`
Hawaiian/Other PI		`0% ( 0)`	`0% ( 0)`	`0% ( 1)`	`0% ( 1)`	`0% ( 0)`	`0% ( 2)`
Black		`7% ( 36)`	`8% ( 23)`	`3% ( 10)`	`4% ( 29)`	`5% ( 18)`	`5% ( 116)`
White		`91% ( 467)`	`85% ( 257)`	`93% ( 364)`	`93% ( 602)`	`92% ( 358)`	`91% (2048)`
More than one		`0% ( 2)`	`3% ( 10)`	`2% ( 7)`	`0% ( 3)`	`1% ( 4)`	`1% ( 26)`
Unknown		`0% ( 0)`	`0% ( 1)`	`1% ( 4)`	`0% ( 1)`	`0% ( 0)`	`0% ( 6)`
CDR-SB	2263	`0.00/0.00/0.00`	`0.00/0.00/0.00`	`0.50/1.00/2.00`	`1.00/1.50/2.00`	`3.50/4.50/5.00`	`0.00/1.00/2.25`	F=2895 d.f.=4,2244 P<0.001
ADAS 13	2243	`6.92/ 9.67/13.00`	`8.67/11.16/14.33`	`9.00/14.00/17.00`	`14.67/19.00/23.67`	`24.41/29.50/35.00`	`10.00/15.00/22.33`	F=649 d.f.=4,2227 P<0.001
MMSE	2263	`29/29/30`	`29/29/30`	`28/29/29`	`26/27/29`	`21/23/25`	`26/28/29`	F=585 d.f.=4,2244 P<0.001

Baseline box plots

dd1 <- subset(dd, VISCODE == "bl" & !is.na(DX.bl), c("RID", "DX.bl", "ADAS13", "CDRSB", 
    "MMSE", "EcogPtMem", "EcogSPMem", "EcogPtTotal", "EcogSPTotal"))
ggplot(dd1, aes(DX.bl, ADAS13)) + geom_boxplot(aes(fill = DX.bl), outlier.shape = NA) + 
    geom_jitter(size = 1, position = position_jitter(h = 0)) + theme(legend.position = "none")

ggplot(dd1, aes(DX.bl, MMSE)) + geom_boxplot(aes(fill = DX.bl), outlier.shape = NA) + 
    geom_jitter(size = 1, position = position_jitter(h = 0)) + theme(legend.position = "none")

ggplot(dd1, aes(DX.bl, CDRSB)) + geom_boxplot(aes(fill = DX.bl), outlier.shape = NA) + 
    geom_jitter(size = 1, position = position_jitter(h = 0)) + theme(legend.position = "none")

ggplot(dd1, aes(DX.bl, EcogPtMem)) + geom_boxplot(aes(fill = DX.bl), outlier.shape = NA) + 
    geom_jitter(size = 1, position = position_jitter(h = 0)) + theme(legend.position = "none") + 
    ylab("ECog Self Memory")

ggplot(dd1, aes(DX.bl, EcogSPMem)) + geom_boxplot(aes(fill = DX.bl), outlier.shape = NA) + 
    geom_jitter(size = 1, position = position_jitter(h = 0)) + theme(legend.position = "none") + 
    ylab("ECog Partner Memory")

ggplot(dd1, aes(DX.bl, EcogPtTotal)) + geom_boxplot(aes(fill = DX.bl), outlier.shape = NA) + 
    geom_jitter(size = 1, position = position_jitter(h = 0)) + theme(legend.position = "none") + 
    ylab("ECog Self Total")

ggplot(dd1, aes(DX.bl, EcogSPTotal)) + geom_boxplot(aes(fill = DX.bl), outlier.shape = NA) + 
    geom_jitter(size = 1, position = position_jitter(h = 0)) + theme(legend.position = "none") + 
    ylab("ECog Partner Total")

Baseline summary statistics

cols <- c("ADAS13", "MMSE", "CDRSB", "EcogPtMem", "EcogPtTotal", "EcogSPTotal")
for (cc in cols) {
    dd1$x <- dd1[, cc]
    tab <- with(dd1, Hmisc::summarize(x, by = DX.bl, FUN = summary.default, stat.name = "N"))
    cat("\n### ", label(dd1[, cc]), "\n")
    rownames(tab) <- tab[, 1]
    kable(tab[, -1])
}


###  ADAS 13 

###  MMSE 

###  CDR-SB 

###  Pt ECog - Mem 

###  Pt ECog - Total 

###  SP ECog - Total

Longitudinal plots


\clearpage
\subsection{ ADAS 13 change from baseline}

%latex.default(tab[, -(1:2)], file = "", rowlabel = "Month", rowname = tab[,     1], rgroup = unique(tab[, 2]), n.rgroup = table(tab[, 2]),     digits = 3, where = "h!", rownamesTexCmd = rcmd, label = paste("long",         oc, sep = ""))%
\begin{table}[h!]
\begin{center}
\begin{tabular}{lrrrrrrrr}
\hline\hline
\multicolumn{1}{l}{Month}&\multicolumn{1}{c}{N}&\multicolumn{1}{c}{Min.}&\multicolumn{1}{c}{Q.1}&\multicolumn{1}{c}{Median}&\multicolumn{1}{c}{Mean}&\multicolumn{1}{c}{Q.3}&\multicolumn{1}{c}{Max.}&\multicolumn{1}{c}{SD}\tabularnewline
\hline
{\bfseries CN}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $270$&   $-11.00$&   $-2.000$&   $ 0.00$&   $-0.3850$&   $ 2.00$&   $11.0$&   $ 3.43$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $265$&   $-11.00$&   $-3.000$&   $-0.33$&   $-0.5170$&   $ 2.00$&   $11.0$&   $ 3.72$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $377$&   $-10.00$&   $-2.000$&   $ 0.00$&   $-0.3080$&   $ 2.00$&   $13.3$&   $ 3.49$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 48$&   $ -9.33$&   $-2.000$&   $ 0.00$&   $-0.1110$&   $ 2.00$&   $11.0$&   $ 3.99$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $162$&   $ -8.00$&   $-2.000$&   $ 1.84$&   $ 1.4000$&   $ 4.00$&   $15.0$&   $ 4.64$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 53$&   $ -1.67$&   $ 2.670$&   $ 4.33$&   $ 5.1500$&   $ 7.00$&   $18.0$&   $ 4.47$\tabularnewline
   ~~72&   $119$&   $ -2.67$&   $ 2.000$&   $ 4.67$&   $ 5.4700$&   $ 7.67$&   $23.7$&   $ 4.65$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 56$&   $ -4.33$&   $ 3.250$&   $ 5.84$&   $ 7.0300$&   $ 8.75$&   $28.3$&   $ 6.28$\tabularnewline
   ~~96&   $ 47$&   $ -5.33$&   $ 2.340$&   $ 5.67$&   $ 5.8700$&   $ 9.50$&   $23.0$&   $ 5.40$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 10$&   $  2.67$&   $ 5.330$&   $ 7.00$&   $ 7.4300$&   $10.20$&   $13.0$&   $ 3.45$\tabularnewline
   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $429$&   $-12.00$&   $-3.000$&   $ 0.00$&   $ 0.0583$&   $ 3.00$&   $16.0$&   $ 4.38$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $532$&   $-15.00$&   $-3.000$&   $ 0.00$&   $ 0.1450$&   $ 3.00$&   $54.0$&   $ 5.02$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $413$&   $-11.00$&   $-2.000$&   $ 0.33$&   $ 1.2300$&   $ 4.00$&   $21.0$&   $ 5.49$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $324$&   $-14.00$&   $-2.000$&   $ 1.00$&   $ 2.0200$&   $ 5.00$&   $49.0$&   $ 7.39$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $253$&   $-12.00$&   $-2.000$&   $ 1.00$&   $ 3.4400$&   $ 6.00$&   $55.0$&   $ 9.58$\tabularnewline
   ~~60&   $139$&   $ -7.00$&   $ 0.000$&   $ 3.00$&   $ 5.5000$&   $ 8.16$&   $71.0$&   $10.90$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $101$&   $ -5.00$&   $ 2.000$&   $ 4.67$&   $ 5.7600$&   $ 8.00$&   $37.0$&   $ 6.79$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 89$&   $ -3.33$&   $ 2.670$&   $ 5.67$&   $ 7.0300$&   $ 9.67$&   $24.7$&   $ 6.34$\tabularnewline
   ~~96&   $ 73$&   $ -5.00$&   $ 3.000$&   $ 6.00$&   $ 7.9600$&   $11.30$&   $38.7$&   $ 7.76$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 31$&   $ -5.67$&   $ 2.840$&   $ 3.67$&   $ 6.3300$&   $ 8.50$&   $25.0$&   $ 6.37$\tabularnewline
   ~~120&   $  9$&   $  0.67$&   $ 3.330$&   $ 4.67$&   $ 8.8900$&   $13.30$&   $25.0$&   $ 8.61$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $127$&   $-12.00$&   $-1.500$&   $ 2.00$&   $ 2.3800$&   $ 6.50$&   $23.0$&   $ 5.62$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $136$&   $-13.00$&   $ 0.247$&   $ 3.34$&   $ 4.6200$&   $ 8.00$&   $27.0$&   $ 6.34$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 43$&   $ -5.00$&   $ 2.660$&   $ 7.00$&   $ 8.3900$&   $12.50$&   $36.0$&   $ 8.83$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  1$&   $  8.00$&   $ 8.000$&   $ 8.00$&   $ 8.0000$&   $ 8.00$&   $ 8.0$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  2$&   $  6.33$&   $ 7.410$&   $ 8.50$&   $ 8.5000$&   $ 9.59$&   $10.7$&   $ 3.07$\tabularnewline
   ~~72&   $  1$&   $ 10.00$&   $10.000$&   $10.00$&   $10.0000$&   $10.00$&   $10.0$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~96&   $  1$&   $ 12.00$&   $12.000$&   $12.00$&   $12.0000$&   $12.00$&   $12.0$&   $$\tabularnewline
\hline
\end{tabular}\end{center}
\end{table}


\clearpage
\subsection{ MMSE change from baseline}

%latex.default(tab[, -(1:2)], file = "", rowlabel = "Month", rowname = tab[,     1], rgroup = unique(tab[, 2]), n.rgroup = table(tab[, 2]),     digits = 3, where = "h!", rownamesTexCmd = rcmd, label = paste("long",         oc, sep = ""))%
\begin{table}[h!]
\begin{center}
\begin{tabular}{lrrrrrrrr}
\hline\hline
\multicolumn{1}{l}{Month}&\multicolumn{1}{c}{N}&\multicolumn{1}{c}{Min.}&\multicolumn{1}{c}{Q.1}&\multicolumn{1}{c}{Median}&\multicolumn{1}{c}{Mean}&\multicolumn{1}{c}{Q.3}&\multicolumn{1}{c}{Max.}&\multicolumn{1}{c}{SD}\tabularnewline
\hline
{\bfseries CN}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $274$&   $ -4$&   $-1.00$&   $ 0.0$&   $-0.0547$&   $ 1.00$&   $ 4$&   $1.40$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $267$&   $ -8$&   $-1.00$&   $ 0.0$&   $-0.2170$&   $ 1.00$&   $ 4$&   $1.59$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $385$&   $ -5$&   $-1.00$&   $ 0.0$&   $-0.1120$&   $ 1.00$&   $ 4$&   $1.42$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 51$&   $ -5$&   $-1.00$&   $ 0.0$&   $-0.4120$&   $ 1.00$&   $ 4$&   $1.78$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $162$&   $ -7$&   $-1.00$&   $ 0.0$&   $-0.2840$&   $ 1.00$&   $ 4$&   $1.69$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 53$&   $-10$&   $-1.00$&   $ 0.0$&   $-0.1890$&   $ 0.00$&   $ 4$&   $1.97$\tabularnewline
   ~~72&   $118$&   $ -8$&   $-1.00$&   $ 0.0$&   $-0.3310$&   $ 1.00$&   $ 4$&   $1.91$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 55$&   $ -7$&   $-2.00$&   $ 0.0$&   $-1.0000$&   $ 0.00$&   $ 3$&   $1.93$\tabularnewline
   ~~96&   $ 48$&   $ -4$&   $-1.25$&   $ 0.0$&   $-0.4170$&   $ 0.25$&   $ 4$&   $1.64$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 10$&   $ -3$&   $-1.50$&   $ 0.0$&   $-0.4000$&   $ 0.00$&   $ 2$&   $1.51$\tabularnewline
   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $430$&   $-10$&   $-2.00$&   $ 0.0$&   $-0.4490$&   $ 1.00$&   $ 5$&   $1.88$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $537$&   $-11$&   $-2.00$&   $ 0.0$&   $-0.5380$&   $ 1.00$&   $ 6$&   $2.12$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $419$&   $-12$&   $-2.00$&   $ 0.0$&   $-0.9310$&   $ 1.00$&   $ 6$&   $2.50$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $325$&   $-23$&   $-2.00$&   $-1.0$&   $-1.2500$&   $ 1.00$&   $ 6$&   $3.29$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $257$&   $-20$&   $-3.00$&   $-1.0$&   $-1.6000$&   $ 1.00$&   $ 5$&   $3.81$\tabularnewline
   ~~60&   $143$&   $-30$&   $-3.00$&   $-1.0$&   $-1.9900$&   $ 0.00$&   $ 4$&   $4.64$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $105$&   $-24$&   $-2.00$&   $ 0.0$&   $-1.5000$&   $ 1.00$&   $ 5$&   $4.17$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 94$&   $-20$&   $-3.00$&   $-1.0$&   $-1.8000$&   $ 1.00$&   $ 6$&   $4.32$\tabularnewline
   ~~96&   $ 74$&   $-12$&   $-3.00$&   $-1.0$&   $-1.6900$&   $ 1.00$&   $ 5$&   $3.60$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 32$&   $ -5$&   $-2.00$&   $-0.5$&   $-0.9380$&   $ 0.00$&   $ 2$&   $1.85$\tabularnewline
   ~~120&   $ 10$&   $ -5$&   $-2.00$&   $-0.5$&   $-0.8000$&   $ 1.00$&   $ 2$&   $2.44$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $131$&   $-16$&   $-3.00$&   $-1.0$&   $-1.1800$&   $ 1.00$&   $ 8$&   $3.07$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $141$&   $-19$&   $-5.00$&   $-2.0$&   $-2.5200$&   $ 0.00$&   $ 5$&   $4.14$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 44$&   $-15$&   $-6.25$&   $-4.0$&   $-4.3000$&   $-2.00$&   $ 3$&   $3.89$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  1$&   $ -2$&   $-2.00$&   $-2.0$&   $-2.0000$&   $-2.00$&   $-2$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  2$&   $ -4$&   $-3.00$&   $-2.0$&   $-2.0000$&   $-1.00$&   $ 0$&   $2.83$\tabularnewline
   ~~72&   $  2$&   $ -5$&   $-4.50$&   $-4.0$&   $-4.0000$&   $-3.50$&   $-3$&   $1.41$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  1$&   $ -5$&   $-5.00$&   $-5.0$&   $-5.0000$&   $-5.00$&   $-5$&   $$\tabularnewline
   ~~96&   $  1$&   $ -8$&   $-8.00$&   $-8.0$&   $-8.0000$&   $-8.00$&   $-8$&   $$\tabularnewline
\hline
\end{tabular}\end{center}
\end{table}


\clearpage
\subsection{ CDR-SB change from baseline}

%latex.default(tab[, -(1:2)], file = "", rowlabel = "Month", rowname = tab[,     1], rgroup = unique(tab[, 2]), n.rgroup = table(tab[, 2]),     digits = 3, where = "h!", rownamesTexCmd = rcmd, label = paste("long",         oc, sep = ""))%
\begin{table}[h!]
\begin{center}
\begin{tabular}{lrrrrrrrr}
\hline\hline
\multicolumn{1}{l}{Month}&\multicolumn{1}{c}{N}&\multicolumn{1}{c}{Min.}&\multicolumn{1}{c}{Q.1}&\multicolumn{1}{c}{Median}&\multicolumn{1}{c}{Mean}&\multicolumn{1}{c}{Q.3}&\multicolumn{1}{c}{Max.}&\multicolumn{1}{c}{SD}\tabularnewline
\hline
{\bfseries CN}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.0$&   $ 0.000$&   $ 0.00$&   $ 0.0879$&   $ 0.00$&   $ 2.5$&   $0.348$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $265$&   $-1.0$&   $ 0.000$&   $ 0.00$&   $ 0.1260$&   $ 0.00$&   $ 4.0$&   $0.492$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $408$&   $-1.0$&   $ 0.000$&   $ 0.00$&   $ 0.1480$&   $ 0.00$&   $ 5.0$&   $0.555$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 48$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.5210$&   $ 0.50$&   $ 5.0$&   $1.160$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $157$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.2130$&   $ 0.00$&   $ 5.0$&   $0.698$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 56$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.5540$&   $ 0.50$&   $11.0$&   $1.710$\tabularnewline
   ~~72&   $123$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.4270$&   $ 0.25$&   $10.0$&   $1.240$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 65$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.8380$&   $ 1.00$&   $12.0$&   $1.940$\tabularnewline
   ~~96&   $ 51$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.7060$&   $ 0.50$&   $15.5$&   $2.290$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 15$&   $ 0.0$&   $ 0.000$&   $ 0.00$&   $ 2.2300$&   $ 1.00$&   $17.5$&   $4.770$\tabularnewline
   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $426$&   $-3.5$&   $-0.500$&   $ 0.00$&   $ 0.1310$&   $ 0.50$&   $ 3.0$&   $0.807$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $536$&   $-3.0$&   $-0.500$&   $ 0.00$&   $ 0.2160$&   $ 0.50$&   $ 9.0$&   $1.100$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $434$&   $-3.0$&   $-0.500$&   $ 0.00$&   $ 0.6000$&   $ 1.00$&   $11.5$&   $1.640$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $337$&   $-3.5$&   $-0.500$&   $ 0.00$&   $ 0.8740$&   $ 1.50$&   $12.5$&   $2.350$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $258$&   $-3.5$&   $-0.500$&   $ 0.00$&   $ 1.1100$&   $ 2.00$&   $16.0$&   $2.910$\tabularnewline
   ~~60&   $141$&   $-3.0$&   $-0.500$&   $ 0.00$&   $ 0.9260$&   $ 1.50$&   $14.5$&   $2.650$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $109$&   $-3.0$&   $-0.500$&   $ 0.00$&   $ 1.2200$&   $ 1.50$&   $15.5$&   $3.430$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 96$&   $-3.5$&   $-0.500$&   $ 0.25$&   $ 1.3500$&   $ 1.62$&   $15.0$&   $3.400$\tabularnewline
   ~~96&   $ 81$&   $-3.5$&   $-0.500$&   $ 0.00$&   $ 1.3300$&   $ 1.50$&   $14.0$&   $3.490$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 44$&   $-2.5$&   $-0.500$&   $ 0.00$&   $ 1.2800$&   $ 1.50$&   $16.5$&   $3.480$\tabularnewline
   ~~120&   $ 12$&   $-1.5$&   $-0.625$&   $-0.25$&   $ 0.2500$&   $ 1.50$&   $ 2.5$&   $1.320$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $131$&   $-2.5$&   $ 0.000$&   $ 0.50$&   $ 0.8130$&   $ 1.50$&   $ 9.0$&   $1.540$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $151$&   $-2.0$&   $ 0.000$&   $ 1.00$&   $ 1.8700$&   $ 2.50$&   $11.5$&   $2.470$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 48$&   $-1.0$&   $ 1.000$&   $ 2.50$&   $ 3.2000$&   $ 5.00$&   $11.5$&   $2.810$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  1$&   $ 2.0$&   $ 2.000$&   $ 2.00$&   $ 2.0000$&   $ 2.00$&   $ 2.0$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  1$&   $ 3.0$&   $ 3.000$&   $ 3.00$&   $ 3.0000$&   $ 3.00$&   $ 3.0$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  4$&   $ 2.0$&   $ 4.250$&   $ 8.00$&   $ 7.3800$&   $11.10$&   $11.5$&   $4.640$\tabularnewline
   ~~72&   $  4$&   $ 7.0$&   $ 8.120$&   $10.00$&   $10.4000$&   $12.20$&   $14.5$&   $3.330$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  1$&   $ 4.0$&   $ 4.000$&   $ 4.00$&   $ 4.0000$&   $ 4.00$&   $ 4.0$&   $$\tabularnewline
   ~~96&   $  1$&   $11.0$&   $11.000$&   $11.00$&   $11.0000$&   $11.00$&   $11.0$&   $$\tabularnewline
\hline
\end{tabular}\end{center}
\end{table}


\clearpage
\subsection{ Pt ECog - Mem change from baseline}

%latex.default(tab[, -(1:2)], file = "", rowlabel = "Month", rowname = tab[,     1], rgroup = unique(tab[, 2]), n.rgroup = table(tab[, 2]),     digits = 3, where = "h!", rownamesTexCmd = rcmd, label = paste("long",         oc, sep = ""))%
\begin{table}[h!]
\begin{center}
\begin{tabular}{lrrrrrrrr}
\hline\hline
\multicolumn{1}{l}{Month}&\multicolumn{1}{c}{N}&\multicolumn{1}{c}{Min.}&\multicolumn{1}{c}{Q.1}&\multicolumn{1}{c}{Median}&\multicolumn{1}{c}{Mean}&\multicolumn{1}{c}{Q.3}&\multicolumn{1}{c}{Max.}&\multicolumn{1}{c}{SD}\tabularnewline
\hline
{\bfseries CN}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.500$&   $-0.250$&   $ 0.0000$&   $ 0.0303$&   $ 0.250$&   $ 1.6200$&   $0.431$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $269$&   $-1.380$&   $-0.250$&   $ 0.0000$&   $ 0.0229$&   $ 0.250$&   $ 1.6200$&   $0.427$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $416$&   $-2.000$&   $-0.250$&   $ 0.0000$&   $ 0.0161$&   $ 0.250$&   $ 1.7500$&   $0.441$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 50$&   $-0.589$&   $-0.250$&   $ 0.0000$&   $-0.0118$&   $ 0.125$&   $ 0.7500$&   $0.318$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $164$&   $-1.380$&   $-0.250$&   $ 0.0000$&   $ 0.0560$&   $ 0.375$&   $ 2.1200$&   $0.494$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 57$&   $-1.430$&   $ 0.000$&   $ 0.1250$&   $ 0.1460$&   $ 0.375$&   $ 1.3800$&   $0.494$\tabularnewline
   ~~72&   $123$&   $-1.320$&   $-0.125$&   $ 0.1250$&   $ 0.1660$&   $ 0.500$&   $ 1.6200$&   $0.538$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 66$&   $-1.500$&   $-0.219$&   $ 0.1250$&   $ 0.1650$&   $ 0.500$&   $ 1.8200$&   $0.628$\tabularnewline
   ~~96&   $ 53$&   $-1.120$&   $-0.125$&   $ 0.1250$&   $ 0.2320$&   $ 0.500$&   $ 2.2500$&   $0.613$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 13$&   $-0.500$&   $-0.250$&   $ 0.1250$&   $ 0.2310$&   $ 0.500$&   $ 2.0000$&   $0.647$\tabularnewline
   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $428$&   $-2.120$&   $-0.375$&   $-0.1250$&   $-0.1040$&   $ 0.250$&   $ 1.6200$&   $0.539$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $541$&   $-2.250$&   $-0.375$&   $ 0.0000$&   $-0.0663$&   $ 0.250$&   $ 1.6200$&   $0.599$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $431$&   $-2.880$&   $-0.375$&   $ 0.0000$&   $-0.0248$&   $ 0.375$&   $ 2.5000$&   $0.652$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $330$&   $-2.380$&   $-0.375$&   $-0.0357$&   $-0.0382$&   $ 0.375$&   $ 2.5000$&   $0.635$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $251$&   $-2.500$&   $-0.500$&   $-0.1250$&   $-0.1030$&   $ 0.304$&   $ 2.3600$&   $0.728$\tabularnewline
   ~~60&   $141$&   $-1.500$&   $-0.375$&   $ 0.0000$&   $ 0.0201$&   $ 0.500$&   $ 1.7500$&   $0.596$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $103$&   $-2.120$&   $-0.375$&   $ 0.0000$&   $ 0.0223$&   $ 0.500$&   $ 1.7500$&   $0.742$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 96$&   $-2.380$&   $-0.375$&   $-0.1250$&   $-0.0655$&   $ 0.250$&   $ 2.0000$&   $0.659$\tabularnewline
   ~~96&   $ 80$&   $-2.500$&   $-0.500$&   $-0.2500$&   $-0.1910$&   $ 0.156$&   $ 2.2100$&   $0.701$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 43$&   $-2.250$&   $-0.500$&   $-0.1250$&   $-0.0911$&   $ 0.250$&   $ 1.8800$&   $0.781$\tabularnewline
   ~~120&   $ 12$&   $-1.880$&   $-0.625$&   $-0.3120$&   $-0.2400$&   $ 0.125$&   $ 1.6200$&   $0.852$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $124$&   $-1.880$&   $-0.406$&   $ 0.0000$&   $-0.0592$&   $ 0.375$&   $ 1.7500$&   $0.725$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $128$&   $-2.000$&   $-0.460$&   $-0.0179$&   $-0.1290$&   $ 0.375$&   $ 2.0000$&   $0.733$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 36$&   $-1.750$&   $-0.500$&   $-0.1880$&   $-0.1220$&   $ 0.277$&   $ 2.1200$&   $0.761$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  1$&   $-0.500$&   $-0.500$&   $-0.5000$&   $-0.5000$&   $-0.500$&   $-0.5000$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  2$&   $-0.875$&   $-0.665$&   $-0.4550$&   $-0.4550$&   $-0.246$&   $-0.0357$&   $0.593$\tabularnewline
   ~~72&   $  1$&   $-0.875$&   $-0.875$&   $-0.8750$&   $-0.8750$&   $-0.875$&   $-0.8750$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~96&   $  1$&   $-1.620$&   $-1.620$&   $-1.6200$&   $-1.6200$&   $-1.620$&   $-1.6200$&   $$\tabularnewline
\hline
\end{tabular}\end{center}
\end{table}


\clearpage
\subsection{ SP ECog - Mem change from baseline}

%latex.default(tab[, -(1:2)], file = "", rowlabel = "Month", rowname = tab[,     1], rgroup = unique(tab[, 2]), n.rgroup = table(tab[, 2]),     digits = 3, where = "h!", rownamesTexCmd = rcmd, label = paste("long",         oc, sep = ""))%
\begin{table}[h!]
\begin{center}
\begin{tabular}{lrrrrrrrr}
\hline\hline
\multicolumn{1}{l}{Month}&\multicolumn{1}{c}{N}&\multicolumn{1}{c}{Min.}&\multicolumn{1}{c}{Q.1}&\multicolumn{1}{c}{Median}&\multicolumn{1}{c}{Mean}&\multicolumn{1}{c}{Q.3}&\multicolumn{1}{c}{Max.}&\multicolumn{1}{c}{SD}\tabularnewline
\hline
{\bfseries CN}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $263$&   $-1.380$&   $-0.1250$&   $0.000$&   $0.01720$&   $0.125$&   $1.62$&   $0.361$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $263$&   $-1.500$&   $-0.1250$&   $0.000$&   $0.04230$&   $0.250$&   $2.12$&   $0.406$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $399$&   $-1.500$&   $-0.1250$&   $0.000$&   $0.04400$&   $0.250$&   $2.12$&   $0.416$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 47$&   $-1.380$&   $-0.1250$&   $0.125$&   $0.18300$&   $0.375$&   $2.12$&   $0.586$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $156$&   $-1.250$&   $-0.1490$&   $0.000$&   $0.11300$&   $0.250$&   $2.12$&   $0.489$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 54$&   $-0.750$&   $-0.1250$&   $0.000$&   $0.14100$&   $0.250$&   $2.46$&   $0.568$\tabularnewline
   ~~72&   $123$&   $-1.500$&   $-0.1250$&   $0.000$&   $0.20600$&   $0.438$&   $2.25$&   $0.621$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 65$&   $-2.380$&   $-0.1250$&   $0.125$&   $0.35000$&   $0.625$&   $2.75$&   $0.866$\tabularnewline
   ~~96&   $ 51$&   $-1.380$&   $-0.1250$&   $0.000$&   $0.24600$&   $0.500$&   $3.00$&   $0.671$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 15$&   $-0.125$&   $ 0.0625$&   $0.625$&   $0.93300$&   $1.190$&   $3.00$&   $1.080$\tabularnewline
   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $424$&   $-1.880$&   $-0.2500$&   $0.000$&   $0.00345$&   $0.375$&   $2.12$&   $0.561$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $535$&   $-2.750$&   $-0.2500$&   $0.000$&   $0.01400$&   $0.327$&   $2.25$&   $0.586$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $434$&   $-1.880$&   $-0.2500$&   $0.000$&   $0.10600$&   $0.500$&   $2.12$&   $0.657$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $329$&   $-2.250$&   $-0.2500$&   $0.125$&   $0.14900$&   $0.500$&   $2.14$&   $0.703$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $245$&   $-1.750$&   $-0.2500$&   $0.125$&   $0.22500$&   $0.500$&   $2.88$&   $0.710$\tabularnewline
   ~~60&   $137$&   $-1.620$&   $-0.1790$&   $0.125$&   $0.27000$&   $0.625$&   $2.50$&   $0.783$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $109$&   $-1.620$&   $-0.2500$&   $0.125$&   $0.20200$&   $0.625$&   $2.29$&   $0.697$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 99$&   $-1.250$&   $-0.2590$&   $0.125$&   $0.26400$&   $0.750$&   $2.50$&   $0.820$\tabularnewline
   ~~96&   $ 80$&   $-2.000$&   $-0.1880$&   $0.250$&   $0.25700$&   $0.625$&   $2.38$&   $0.768$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 44$&   $-0.750$&   $-0.2500$&   $0.312$&   $0.34600$&   $0.750$&   $2.50$&   $0.692$\tabularnewline
   ~~120&   $ 11$&   $-0.857$&   $-0.4020$&   $0.000$&   $0.15400$&   $0.741$&   $1.50$&   $0.737$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $130$&   $-2.750$&   $-0.2500$&   $0.000$&   $0.04210$&   $0.479$&   $1.62$&   $0.616$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $149$&   $-1.620$&   $ 0.0000$&   $0.125$&   $0.21500$&   $0.500$&   $2.12$&   $0.513$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 49$&   $-1.750$&   $ 0.0000$&   $0.000$&   $0.11700$&   $0.375$&   $1.50$&   $0.613$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  1$&   $ 1.250$&   $ 1.2500$&   $1.250$&   $1.25000$&   $1.250$&   $1.25$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  1$&   $ 0.000$&   $ 0.0000$&   $0.000$&   $0.00000$&   $0.000$&   $0.00$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  4$&   $ 0.000$&   $ 0.0938$&   $0.625$&   $0.84400$&   $1.380$&   $2.12$&   $0.992$\tabularnewline
   ~~72&   $  4$&   $ 0.000$&   $ 0.8440$&   $1.470$&   $1.27000$&   $1.900$&   $2.12$&   $0.943$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  1$&   $ 0.000$&   $ 0.0000$&   $0.000$&   $0.00000$&   $0.000$&   $0.00$&   $$\tabularnewline
   ~~96&   $  1$&   $ 2.000$&   $ 2.0000$&   $2.000$&   $2.00000$&   $2.000$&   $2.00$&   $$\tabularnewline
\hline
\end{tabular}\end{center}
\end{table}


\clearpage
\subsection{ Pt ECog - Total change from baseline}

%latex.default(tab[, -(1:2)], file = "", rowlabel = "Month", rowname = tab[,     1], rgroup = unique(tab[, 2]), n.rgroup = table(tab[, 2]),     digits = 3, where = "h!", rownamesTexCmd = rcmd, label = paste("long",         oc, sep = ""))%
\begin{table}[h!]
\begin{center}
\begin{tabular}{lrrrrrrrr}
\hline\hline
\multicolumn{1}{l}{Month}&\multicolumn{1}{c}{N}&\multicolumn{1}{c}{Min.}&\multicolumn{1}{c}{Q.1}&\multicolumn{1}{c}{Median}&\multicolumn{1}{c}{Mean}&\multicolumn{1}{c}{Q.3}&\multicolumn{1}{c}{Max.}&\multicolumn{1}{c}{SD}\tabularnewline
\hline
{\bfseries CN}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.140$&   $-0.1030$&   $ 0.00000$&   $ 0.017800$&   $ 0.1280$&   $ 0.8210$&   $0.253$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $269$&   $-0.751$&   $-0.1030$&   $ 0.00000$&   $ 0.028900$&   $ 0.1280$&   $ 1.4600$&   $0.253$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $416$&   $-1.340$&   $-0.1030$&   $ 0.00000$&   $ 0.014200$&   $ 0.1320$&   $ 1.1800$&   $0.293$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 50$&   $-0.526$&   $-0.0982$&   $-0.01280$&   $ 0.028700$&   $ 0.1470$&   $ 0.7440$&   $0.235$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $165$&   $-0.985$&   $-0.1190$&   $ 0.03850$&   $ 0.041000$&   $ 0.1630$&   $ 1.7200$&   $0.304$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 57$&   $-0.725$&   $-0.0466$&   $ 0.13300$&   $ 0.112000$&   $ 0.2210$&   $ 0.7270$&   $0.314$\tabularnewline
   ~~72&   $123$&   $-1.010$&   $-0.0334$&   $ 0.10500$&   $ 0.134000$&   $ 0.2570$&   $ 1.3000$&   $0.328$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 66$&   $-0.784$&   $-0.0577$&   $ 0.06010$&   $ 0.112000$&   $ 0.2980$&   $ 1.1600$&   $0.368$\tabularnewline
   ~~96&   $ 53$&   $-1.110$&   $ 0.0027$&   $ 0.09630$&   $ 0.208000$&   $ 0.2230$&   $ 2.6400$&   $0.523$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 13$&   $-0.254$&   $ 0.0297$&   $ 0.13800$&   $ 0.270000$&   $ 0.4420$&   $ 1.6600$&   $0.476$\tabularnewline
   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $430$&   $-2.080$&   $-0.2190$&   $-0.02630$&   $-0.035000$&   $ 0.1500$&   $ 1.5900$&   $0.376$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $544$&   $-1.690$&   $-0.2310$&   $-0.01960$&   $-0.020800$&   $ 0.1850$&   $ 1.6700$&   $0.396$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $433$&   $-1.690$&   $-0.2050$&   $ 0.00000$&   $ 0.023200$&   $ 0.2310$&   $ 1.7400$&   $0.447$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $326$&   $-1.730$&   $-0.2040$&   $ 0.02560$&   $ 0.048800$&   $ 0.3010$&   $ 1.9900$&   $0.456$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $250$&   $-2.310$&   $-0.2540$&   $ 0.02560$&   $ 0.028900$&   $ 0.3010$&   $ 2.7100$&   $0.530$\tabularnewline
   ~~60&   $139$&   $-1.210$&   $-0.1410$&   $ 0.05130$&   $ 0.072500$&   $ 0.3260$&   $ 1.1300$&   $0.438$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $103$&   $-1.130$&   $-0.1650$&   $ 0.05400$&   $ 0.095300$&   $ 0.3850$&   $ 1.4800$&   $0.467$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 96$&   $-1.090$&   $-0.1990$&   $ 0.00877$&   $ 0.018100$&   $ 0.2020$&   $ 1.6000$&   $0.473$\tabularnewline
   ~~96&   $ 80$&   $-1.090$&   $-0.2530$&   $ 0.00405$&   $ 0.017600$&   $ 0.1840$&   $ 2.5900$&   $0.497$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 43$&   $-0.862$&   $-0.2500$&   $-0.02630$&   $-0.000447$&   $ 0.2340$&   $ 0.7940$&   $0.430$\tabularnewline
   ~~120&   $ 12$&   $-1.370$&   $-0.3810$&   $-0.01350$&   $-0.160000$&   $ 0.0800$&   $ 0.6810$&   $0.535$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $120$&   $-1.690$&   $-0.2980$&   $ 0.02320$&   $-0.011900$&   $ 0.2840$&   $ 1.5100$&   $0.554$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $125$&   $-1.380$&   $-0.3420$&   $-0.00962$&   $ 0.001870$&   $ 0.2890$&   $ 2.1000$&   $0.551$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 36$&   $-1.430$&   $-0.1890$&   $ 0.07790$&   $ 0.093800$&   $ 0.4270$&   $ 2.3200$&   $0.640$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  1$&   $ 0.553$&   $ 0.5530$&   $ 0.55300$&   $ 0.553000$&   $ 0.5530$&   $ 0.5530$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  2$&   $-0.543$&   $-0.3940$&   $-0.24500$&   $-0.245000$&   $-0.0957$&   $ 0.0535$&   $0.422$\tabularnewline
   ~~72&   $  1$&   $-0.191$&   $-0.1910$&   $-0.19100$&   $-0.191000$&   $-0.1910$&   $-0.1910$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~96&   $  1$&   $-0.613$&   $-0.6130$&   $-0.61300$&   $-0.613000$&   $-0.6130$&   $-0.6130$&   $$\tabularnewline
\hline
\end{tabular}\end{center}
\end{table}


\clearpage
\subsection{ SP ECog - Total change from baseline}

%latex.default(tab[, -(1:2)], file = "", rowlabel = "Month", rowname = tab[,     1], rgroup = unique(tab[, 2]), n.rgroup = table(tab[, 2]),     digits = 3, where = "h!", rownamesTexCmd = rcmd, label = paste("long",         oc, sep = ""))%
\begin{table}[h!]
\begin{center}
\begin{tabular}{lrrrrrrrr}
\hline\hline
\multicolumn{1}{l}{Month}&\multicolumn{1}{c}{N}&\multicolumn{1}{c}{Min.}&\multicolumn{1}{c}{Q.1}&\multicolumn{1}{c}{Median}&\multicolumn{1}{c}{Mean}&\multicolumn{1}{c}{Q.3}&\multicolumn{1}{c}{Max.}&\multicolumn{1}{c}{SD}\tabularnewline
\hline
{\bfseries CN}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $265$&   $-0.8790$&   $-0.0513$&   $ 0.0000$&   $ 0.00909$&   $ 0.0769$&   $ 0.8460$&   $0.193$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $263$&   $-1.2100$&   $-0.0328$&   $ 0.0000$&   $ 0.03960$&   $ 0.0979$&   $ 1.6200$&   $0.257$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $399$&   $-1.1300$&   $-0.0526$&   $ 0.0000$&   $ 0.03880$&   $ 0.1030$&   $ 2.0000$&   $0.271$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 47$&   $-1.3300$&   $ 0.0000$&   $ 0.0756$&   $ 0.14000$&   $ 0.2060$&   $ 2.0500$&   $0.461$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $157$&   $-1.0500$&   $-0.0513$&   $ 0.0000$&   $ 0.08560$&   $ 0.1280$&   $ 1.6800$&   $0.340$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 54$&   $-0.5400$&   $-0.0447$&   $ 0.0395$&   $ 0.16500$&   $ 0.2110$&   $ 2.5400$&   $0.509$\tabularnewline
   ~~72&   $122$&   $-0.9940$&   $-0.0499$&   $ 0.0526$&   $ 0.16800$&   $ 0.2770$&   $ 2.5200$&   $0.462$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 65$&   $-1.5400$&   $ 0.0000$&   $ 0.1050$&   $ 0.29800$&   $ 0.2910$&   $ 2.9500$&   $0.736$\tabularnewline
   ~~96&   $ 51$&   $-0.9940$&   $-0.0381$&   $ 0.0526$&   $ 0.11000$&   $ 0.1590$&   $ 2.4700$&   $0.463$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 15$&   $-0.0301$&   $ 0.0673$&   $ 0.3440$&   $ 0.76100$&   $ 0.8110$&   $ 2.8700$&   $1.040$\tabularnewline
   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $426$&   $-1.4600$&   $-0.1670$&   $ 0.0206$&   $ 0.05150$&   $ 0.2540$&   $ 1.9900$&   $0.411$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $535$&   $-2.0400$&   $-0.1300$&   $ 0.0513$&   $ 0.08460$&   $ 0.2830$&   $ 2.0900$&   $0.458$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $435$&   $-1.4100$&   $-0.1050$&   $ 0.1150$&   $ 0.19300$&   $ 0.4100$&   $ 2.4100$&   $0.538$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $328$&   $-2.1400$&   $-0.1030$&   $ 0.1440$&   $ 0.24800$&   $ 0.4870$&   $ 2.5100$&   $0.612$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $245$&   $-2.1100$&   $-0.1030$&   $ 0.1540$&   $ 0.28400$&   $ 0.5710$&   $ 2.6200$&   $0.648$\tabularnewline
   ~~60&   $137$&   $-1.0500$&   $-0.1030$&   $ 0.1660$&   $ 0.32500$&   $ 0.6910$&   $ 2.4000$&   $0.676$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $109$&   $-1.1000$&   $-0.1010$&   $ 0.1520$&   $ 0.26500$&   $ 0.5200$&   $ 2.2500$&   $0.622$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 99$&   $-1.3400$&   $-0.0974$&   $ 0.1580$&   $ 0.38100$&   $ 0.8060$&   $ 2.4000$&   $0.779$\tabularnewline
   ~~96&   $ 80$&   $-1.2100$&   $-0.0488$&   $ 0.1310$&   $ 0.40100$&   $ 0.5990$&   $ 2.5100$&   $0.783$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $ 44$&   $-0.5890$&   $-0.0387$&   $ 0.1630$&   $ 0.42300$&   $ 0.8170$&   $ 2.8200$&   $0.702$\tabularnewline
   ~~120&   $ 11$&   $-0.4090$&   $-0.2080$&   $-0.0980$&   $ 0.00131$&   $ 0.1070$&   $ 0.8360$&   $0.344$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $130$&   $-2.5000$&   $-0.1470$&   $ 0.1260$&   $ 0.10500$&   $ 0.4100$&   $ 1.3300$&   $0.524$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $150$&   $-1.4600$&   $ 0.1040$&   $ 0.3290$&   $ 0.34700$&   $ 0.5990$&   $ 1.5700$&   $0.464$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 49$&   $-0.6490$&   $ 0.1060$&   $ 0.3850$&   $ 0.40800$&   $ 0.7710$&   $ 1.8900$&   $0.509$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  1$&   $ 1.1100$&   $ 1.1100$&   $ 1.1100$&   $ 1.11000$&   $ 1.1100$&   $ 1.1100$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  1$&   $ 0.7180$&   $ 0.7180$&   $ 0.7180$&   $ 0.71800$&   $ 0.7180$&   $ 0.7180$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  4$&   $-0.2410$&   $ 0.4780$&   $ 0.7580$&   $ 0.97900$&   $ 1.2600$&   $ 2.6400$&   $1.200$\tabularnewline
   ~~72&   $  4$&   $ 0.6750$&   $ 1.0100$&   $ 1.2000$&   $ 1.43000$&   $ 1.6200$&   $ 2.6600$&   $0.858$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  1$&   $-0.0385$&   $-0.0385$&   $-0.0385$&   $-0.03850$&   $-0.0385$&   $-0.0385$&   $$\tabularnewline
   ~~96&   $  1$&   $ 1.5700$&   $ 1.5700$&   $ 1.5700$&   $ 1.57000$&   $ 1.5700$&   $ 1.5700$&   $$\tabularnewline
\hline
\end{tabular}\end{center}
\end{table}

R Session Information

{r results = "markup" print(sessionInfo(), locale=FALSE)

ADNI1/GO/2 Enrollment

ATRI Biostatistics

ADNI enrollment summaries using the ADNIMERGE R package

Description

Load required R packages and functions

Demographic Summaries by Diagnosis

Baseline

Demographic Summaries by Diagnosis

Baseline

Baseline box plots

Baseline summary statistics

Longitudinal plots

R Session Information

Contents