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=518)	SMC (N=301)	EMCI (N=391)	LMCI (N=651)	AD (N=398)	Combined (N=2259)	Test Statistic
Age [Years]	2267	`69.9/73.2/77.7`	`66.9/70.2/75.7`	`65.8/71.3/76.5`	`69.2/74.3/79.3`	`70.6/75.3/80.3`	`68.3/73.2/78.3`	F=21.7 d.f.=4,2251 P<0.001
Age : (39,49]	2267	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	Chi-square=168 d.f.=16 P<0.001
(49,59]		`1% ( 5)`	`2% ( 6)`	`4% ( 17)`	`3% ( 21)`	`4% ( 16)`	`3% ( 65)`
(59,69]		`19% ( 99)`	`41% ( 124)`	`36% ( 140)`	`21% ( 136)`	`16% ( 65)`	`25% ( 564)`
(69,79]		`61% ( 317)`	`46% ( 137)`	`43% ( 170)`	`49% ( 318)`	`47% ( 186)`	`50% (1128)`
(79,89]		`18% ( 95)`	`10% ( 30)`	`16% ( 64)`	`26% ( 171)`	`31% ( 124)`	`21% ( 484)`
(89,99]		`0% ( 1)`	`1% ( 4)`	`0% ( 0)`	`0% ( 3)`	`2% ( 7)`	`1% ( 15)`
(99,109]		`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`
Sex : Male	2270	`47% ( 244)`	`39% ( 116)`	`56% ( 219)`	`61% ( 397)`	`56% ( 223)`	`53% (1199)`	Chi-square=52 d.f.=4 P<0.001
Education	2270	`14/16/18`	`16/17/18`	`14/16/18`	`14/16/18`	`13/16/18`	`14/16/18`	F=15.6 d.f.=4,2254 P<0.001
Marital : Divorced	2270	`10% ( 54)`	`13% ( 39)`	`11% ( 43)`	`8% ( 53)`	`4% ( 14)`	`9% ( 203)`	Chi-square=63.7 d.f.=16 P<0.001
Married		`69% ( 360)`	`72% ( 216)`	`77% ( 302)`	`78% ( 507)`	`84% ( 336)`	`76% (1721)`
Never married		`5% ( 27)`	`5% ( 15)`	`4% ( 16)`	`2% ( 12)`	`3% ( 10)`	`4% ( 80)`
Unknown		`0% ( 1)`	`0% ( 1)`	`1% ( 4)`	`0% ( 2)`	`0% ( 0)`	`0% ( 8)`
Widowed		`15% ( 76)`	`10% ( 30)`	`7% ( 26)`	`12% ( 77)`	`10% ( 38)`	`11% ( 247)`
Ethnicity : Unknown	2270	`0% ( 2)`	`1% ( 2)`	`1% ( 2)`	`0% ( 3)`	`1% ( 3)`	`1% ( 12)`	Chi-square=6.42 d.f.=8 P=0.6
Not Hisp/Latino		`95% ( 494)`	`95% ( 287)`	`94% ( 367)`	`97% ( 630)`	`96% ( 381)`	`96% (2159)`
Hisp/Latino		`4% ( 22)`	`4% ( 12)`	`6% ( 22)`	`3% ( 18)`	`4% ( 14)`	`4% ( 88)`
Race : Am Indian/Alaskan	2270	`0% ( 2)`	`0% ( 0)`	`0% ( 1)`	`0% ( 1)`	`0% ( 0)`	`0% ( 4)`	Chi-square=50.4 d.f.=24 P=0.001
Asian		`2% ( 9)`	`3% ( 9)`	`1% ( 5)`	`2% ( 12)`	`3% ( 10)`	`2% ( 45)`
Hawaiian/Other PI		`0% ( 0)`	`0% ( 0)`	`0% ( 1)`	`0% ( 1)`	`0% ( 0)`	`0% ( 2)`
Black		`6% ( 32)`	`7% ( 22)`	`3% ( 10)`	`5% ( 30)`	`5% ( 18)`	`5% ( 112)`
White		`91% ( 473)`	`86% ( 259)`	`93% ( 362)`	`93% ( 603)`	`92% ( 366)`	`91% (2063)`
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	2270	`0.0/0.0/0.0`	`0.0/0.0/0.0`	`0.5/1.0/1.5`	`1.0/1.5/2.0`	`3.5/4.5/5.0`	`0.0/1.0/2.0`	F=2869 d.f.=4,2254 P<0.001
ADAS 13	2247	`6.67/ 9.67/12.67`	`8.33/11.00/14.33`	`9.00/13.00/17.00`	`14.67/18.67/23.33`	`24.67/29.67/35.00`	`10.00/15.00/22.33`	F=666 d.f.=4,2233 P<0.001
MMSE	2270	`29/29/30`	`29/29/30`	`28/29/29`	`26/27/29`	`21/23/25`	`26/28/29`	F=601 d.f.=4,2254 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=511)	SMC (N=298)	EMCI (N=380)	LMCI (N=639)	AD (N=388)	Combined (N=2216)	Test Statistic
Age [Years]	2224	`69.9/73.2/77.7`	`66.8/70.2/75.8`	`66.0/71.5/76.4`	`69.2/74.3/79.2`	`70.5/75.3/80.3`	`68.3/73.2/78.3`	F=20.8 d.f.=4,2208 P<0.001
Age : (39,49]	2224	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	Chi-square=164 d.f.=16 P<0.001
(49,59]		`1% ( 5)`	`2% ( 6)`	`4% ( 16)`	`3% ( 20)`	`4% ( 16)`	`3% ( 63)`
(59,69]		`19% ( 97)`	`41% ( 123)`	`36% ( 135)`	`21% ( 134)`	`16% ( 63)`	`25% ( 552)`
(69,79]		`61% ( 313)`	`45% ( 135)`	`44% ( 167)`	`49% ( 313)`	`47% ( 182)`	`50% (1110)`
(79,89]		`18% ( 94)`	`10% ( 30)`	`16% ( 62)`	`26% ( 167)`	`31% ( 120)`	`21% ( 473)`
(89,99]		`0% ( 1)`	`1% ( 4)`	`0% ( 0)`	`0% ( 3)`	`2% ( 7)`	`1% ( 15)`
(99,109]		`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`
Sex : Male	2227	`47% ( 242)`	`38% ( 114)`	`57% ( 215)`	`61% ( 391)`	`56% ( 218)`	`53% (1180)`	Chi-square=53.3 d.f.=4 P<0.001
Education	2227	`14.0/16.0/18.0`	`15.2/17.0/18.0`	`14.0/16.0/18.0`	`14.0/16.0/18.0`	`13.0/16.0/18.0`	`14.0/16.0/18.0`	F=15.1 d.f.=4,2211 P<0.001
Marital : Divorced	2227	`10% ( 53)`	`13% ( 39)`	`11% ( 41)`	`8% ( 53)`	`4% ( 14)`	`9% ( 200)`	Chi-square=62.7 d.f.=16 P<0.001
Married		`70% ( 357)`	`72% ( 215)`	`78% ( 296)`	`78% ( 497)`	`84% ( 327)`	`76% (1692)`
Never married		`5% ( 26)`	`5% ( 15)`	`4% ( 15)`	`2% ( 11)`	`3% ( 10)`	`3% ( 77)`
Unknown		`0% ( 1)`	`0% ( 1)`	`1% ( 4)`	`0% ( 2)`	`0% ( 0)`	`0% ( 8)`
Widowed		`14% ( 74)`	`9% ( 28)`	`6% ( 24)`	`12% ( 76)`	`10% ( 37)`	`11% ( 239)`
Ethnicity : Unknown	2227	`0% ( 2)`	`1% ( 2)`	`1% ( 2)`	`0% ( 3)`	`1% ( 3)`	`1% ( 12)`	Chi-square=6.67 d.f.=8 P=0.572
Not Hisp/Latino		`95% ( 487)`	`95% ( 284)`	`94% ( 357)`	`97% ( 619)`	`96% ( 372)`	`96% (2119)`
Hisp/Latino		`4% ( 22)`	`4% ( 12)`	`6% ( 21)`	`3% ( 17)`	`3% ( 13)`	`4% ( 85)`
Race : Am Indian/Alaskan	2227	`0% ( 2)`	`0% ( 0)`	`0% ( 1)`	`0% ( 1)`	`0% ( 0)`	`0% ( 4)`	Chi-square=50.8 d.f.=24 P=0.001
Asian		`2% ( 9)`	`3% ( 9)`	`1% ( 5)`	`2% ( 12)`	`3% ( 10)`	`2% ( 45)`
Hawaiian/Other PI		`0% ( 0)`	`0% ( 0)`	`0% ( 1)`	`0% ( 1)`	`0% ( 0)`	`0% ( 2)`
Black		`6% ( 32)`	`7% ( 22)`	`2% ( 9)`	`5% ( 29)`	`5% ( 18)`	`5% ( 110)`
White		`91% ( 466)`	`86% ( 256)`	`93% ( 353)`	`93% ( 592)`	`92% ( 356)`	`91% (2023)`
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	2227	`0.00/0.00/0.00`	`0.00/0.00/0.00`	`0.50/1.00/1.62`	`1.00/1.50/2.00`	`3.50/4.50/5.00`	`0.00/1.00/2.00`	F=2842 d.f.=4,2211 P<0.001
ADAS 13	2208	`6.67/ 9.67/12.67`	`8.50/11.33/14.33`	`9.00/13.00/17.00`	`14.67/18.67/23.33`	`24.33/29.67/35.00`	`10.00/15.00/22.33`	F=649 d.f.=4,2194 P<0.001
MMSE	2227	`29/29/30`	`29/29/30`	`28/29/29`	`26/27/29`	`21/23/25`	`26/28/29`	F=583 d.f.=4,2211 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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $270$&   $-11.00$&   $-2.000$&   $ 0.00$&   $-0.3850$&   $ 2.00$&   $11.00$&   $ 3.43$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $261$&   $-11.00$&   $-3.000$&   $ 0.00$&   $-0.5020$&   $ 2.00$&   $11.00$&   $ 3.74$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $299$&   $-10.00$&   $-2.840$&   $-0.33$&   $-0.4540$&   $ 2.00$&   $10.00$&   $ 3.48$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 42$&   $ -8.00$&   $-2.000$&   $-1.00$&   $-0.2780$&   $ 2.00$&   $11.00$&   $ 3.77$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $161$&   $ -8.00$&   $-2.000$&   $ 1.67$&   $ 1.3600$&   $ 4.00$&   $15.00$&   $ 4.63$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 53$&   $ -1.67$&   $ 2.670$&   $ 4.33$&   $ 5.1300$&   $ 7.00$&   $18.00$&   $ 4.49$\tabularnewline
   ~~72&   $119$&   $ -2.67$&   $ 2.000$&   $ 4.67$&   $ 5.4700$&   $ 7.67$&   $23.70$&   $ 4.65$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 50$&   $ -4.33$&   $ 3.080$&   $ 5.84$&   $ 6.8700$&   $ 7.33$&   $28.30$&   $ 6.35$\tabularnewline
   ~~96&   $ 43$&   $ -5.33$&   $ 1.840$&   $ 5.00$&   $ 5.4100$&   $ 7.33$&   $23.00$&   $ 5.53$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  2$&   $  5.00$&   $ 5.330$&   $ 5.66$&   $ 5.6600$&   $ 6.00$&   $ 6.33$&   $ 0.94$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $429$&   $-12.00$&   $-3.000$&   $ 0.00$&   $ 0.0583$&   $ 3.00$&   $16.00$&   $ 4.38$\tabularnewline
   ~~12&   $508$&   $-15.00$&   $-3.000$&   $ 0.00$&   $ 0.0905$&   $ 3.00$&   $54.00$&   $ 5.04$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $381$&   $-11.00$&   $-3.000$&   $ 0.00$&   $ 1.0900$&   $ 4.00$&   $21.00$&   $ 5.53$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $315$&   $-14.00$&   $-2.000$&   $ 1.00$&   $ 2.0400$&   $ 5.00$&   $49.00$&   $ 7.47$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $252$&   $-12.00$&   $-2.000$&   $ 1.00$&   $ 3.4800$&   $ 6.00$&   $55.00$&   $ 9.57$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $139$&   $ -7.00$&   $ 0.000$&   $ 3.00$&   $ 5.5000$&   $ 8.16$&   $71.00$&   $10.90$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $101$&   $ -5.00$&   $ 2.000$&   $ 4.67$&   $ 5.7600$&   $ 8.00$&   $37.00$&   $ 6.79$\tabularnewline
   ~~84&   $ 88$&   $ -3.33$&   $ 2.670$&   $ 5.34$&   $ 6.8900$&   $ 9.42$&   $24.70$&   $ 6.24$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 56$&   $ -5.00$&   $ 3.580$&   $ 6.33$&   $ 8.3300$&   $10.80$&   $38.70$&   $ 7.78$\tabularnewline
   ~~108&   $ 16$&   $ -0.67$&   $ 3.000$&   $ 5.66$&   $ 6.6000$&   $ 8.66$&   $18.30$&   $ 5.23$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $127$&   $-12.00$&   $-1.500$&   $ 2.00$&   $ 2.3800$&   $ 6.50$&   $23.00$&   $ 5.62$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $126$&   $-13.00$&   $ 0.753$&   $ 3.84$&   $ 4.8000$&   $ 8.25$&   $27.00$&   $ 6.38$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 34$&   $ -5.00$&   $ 2.250$&   $ 7.00$&   $ 8.6200$&   $12.80$&   $36.00$&   $ 9.55$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  2$&   $  6.33$&   $ 7.410$&   $ 8.50$&   $ 8.5000$&   $ 9.59$&   $10.70$&   $ 3.07$\tabularnewline
   ~~72&   $  1$&   $ 10.00$&   $10.000$&   $10.00$&   $10.0000$&   $10.00$&   $10.00$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $274$&   $ -4$&   $-1.00$&   $ 0.0$&   $-0.0547$&   $ 1.00$&   $ 4$&   $1.40$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $264$&   $ -8$&   $-1.00$&   $ 0.0$&   $-0.2120$&   $ 1.00$&   $ 4$&   $1.59$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $306$&   $ -4$&   $-1.00$&   $ 0.0$&   $-0.1570$&   $ 1.00$&   $ 4$&   $1.46$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 45$&   $ -5$&   $-1.00$&   $ 0.0$&   $-0.3780$&   $ 1.00$&   $ 4$&   $1.81$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $161$&   $ -7$&   $-1.00$&   $ 0.0$&   $-0.2730$&   $ 1.00$&   $ 4$&   $1.69$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 53$&   $-10$&   $-1.00$&   $ 0.0$&   $-0.1890$&   $ 0.00$&   $ 4$&   $1.97$\tabularnewline
   ~~72&   $118$&   $ -8$&   $-1.00$&   $ 0.0$&   $-0.3310$&   $ 1.00$&   $ 4$&   $1.91$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 49$&   $ -7$&   $-2.00$&   $ 0.0$&   $-0.9800$&   $ 0.00$&   $ 3$&   $1.96$\tabularnewline
   ~~96&   $ 44$&   $-11$&   $-2.00$&   $ 0.0$&   $-0.5680$&   $ 1.00$&   $ 4$&   $2.33$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  2$&   $ -2$&   $-1.25$&   $-0.5$&   $-0.5000$&   $ 0.25$&   $ 1$&   $2.12$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $430$&   $-10$&   $-2.00$&   $ 0.0$&   $-0.4490$&   $ 1.00$&   $ 5$&   $1.88$\tabularnewline
   ~~12&   $511$&   $-11$&   $-2.00$&   $ 0.0$&   $-0.5190$&   $ 1.00$&   $ 6$&   $2.09$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $387$&   $-11$&   $-2.00$&   $ 0.0$&   $-0.9220$&   $ 1.00$&   $ 6$&   $2.44$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $316$&   $-23$&   $-2.00$&   $-1.0$&   $-1.2400$&   $ 1.00$&   $ 6$&   $3.33$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $256$&   $-20$&   $-3.00$&   $-1.0$&   $-1.6000$&   $ 1.00$&   $ 5$&   $3.82$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $143$&   $-30$&   $-3.00$&   $-1.0$&   $-1.9900$&   $ 0.00$&   $ 4$&   $4.64$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $105$&   $-24$&   $-2.00$&   $ 0.0$&   $-1.5300$&   $ 1.00$&   $ 5$&   $4.23$\tabularnewline
   ~~84&   $ 93$&   $-20$&   $-3.00$&   $-1.0$&   $-1.7300$&   $ 1.00$&   $ 6$&   $4.30$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 57$&   $-12$&   $-2.00$&   $ 0.0$&   $-1.5100$&   $ 1.00$&   $ 5$&   $3.70$\tabularnewline
   ~~108&   $ 17$&   $ -4$&   $-2.00$&   $ 0.0$&   $-0.7060$&   $ 1.00$&   $ 2$&   $1.90$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $131$&   $-16$&   $-3.00$&   $-1.0$&   $-1.1800$&   $ 1.00$&   $ 8$&   $3.07$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $131$&   $-19$&   $-4.50$&   $-2.0$&   $-2.5600$&   $ 0.00$&   $ 5$&   $4.11$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 36$&   $-15$&   $-6.00$&   $-3.5$&   $-4.1400$&   $-2.00$&   $ 3$&   $3.83$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  2$&   $ -4$&   $-3.00$&   $-2.0$&   $-2.0000$&   $-1.00$&   $ 0$&   $2.83$\tabularnewline
   ~~72&   $  2$&   $ -5$&   $-4.50$&   $-4.0$&   $-4.0000$&   $-3.50$&   $-3$&   $1.41$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.0$&   $ 0.00$&   $ 0.00$&   $ 0.0879$&   $ 0.00$&   $ 2.5$&   $0.348$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $260$&   $-1.0$&   $ 0.00$&   $ 0.00$&   $ 0.1290$&   $ 0.00$&   $ 4.0$&   $0.497$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $312$&   $-1.0$&   $ 0.00$&   $ 0.00$&   $ 0.1600$&   $ 0.00$&   $ 5.0$&   $0.584$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 42$&   $-0.5$&   $ 0.00$&   $ 0.00$&   $ 0.4760$&   $ 0.50$&   $ 5.0$&   $1.130$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $156$&   $-0.5$&   $ 0.00$&   $ 0.00$&   $ 0.2020$&   $ 0.00$&   $ 5.0$&   $0.686$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 56$&   $-0.5$&   $ 0.00$&   $ 0.00$&   $ 0.5540$&   $ 0.50$&   $11.0$&   $1.710$\tabularnewline
   ~~72&   $123$&   $-0.5$&   $ 0.00$&   $ 0.00$&   $ 0.4270$&   $ 0.25$&   $10.0$&   $1.240$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 55$&   $-0.5$&   $ 0.00$&   $ 0.00$&   $ 0.6000$&   $ 0.50$&   $ 8.5$&   $1.390$\tabularnewline
   ~~96&   $ 44$&   $-0.5$&   $ 0.00$&   $ 0.00$&   $ 0.7050$&   $ 0.50$&   $15.5$&   $2.410$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  2$&   $ 0.0$&   $ 0.00$&   $ 0.00$&   $ 0.0000$&   $ 0.00$&   $ 0.0$&   $0.000$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $426$&   $-3.5$&   $-0.50$&   $ 0.00$&   $ 0.1310$&   $ 0.50$&   $ 3.0$&   $0.807$\tabularnewline
   ~~12&   $510$&   $-3.0$&   $-0.50$&   $ 0.00$&   $ 0.1950$&   $ 0.50$&   $ 5.5$&   $1.030$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $393$&   $-3.0$&   $-0.50$&   $ 0.00$&   $ 0.5880$&   $ 1.00$&   $11.5$&   $1.670$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $325$&   $-3.5$&   $-0.50$&   $ 0.00$&   $ 0.9080$&   $ 1.50$&   $12.5$&   $2.380$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $257$&   $-3.5$&   $-0.50$&   $ 0.00$&   $ 1.1200$&   $ 2.00$&   $16.0$&   $2.910$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $141$&   $-3.0$&   $-0.50$&   $ 0.00$&   $ 0.9260$&   $ 1.50$&   $14.5$&   $2.650$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $109$&   $-3.0$&   $-0.50$&   $ 0.00$&   $ 1.2200$&   $ 1.50$&   $15.5$&   $3.430$\tabularnewline
   ~~84&   $ 96$&   $-3.5$&   $-0.50$&   $ 0.25$&   $ 1.4400$&   $ 1.62$&   $15.0$&   $3.520$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 68$&   $-3.5$&   $-0.50$&   $ 0.00$&   $ 1.3500$&   $ 1.50$&   $14.0$&   $3.610$\tabularnewline
   ~~108&   $ 19$&   $-2.5$&   $-1.00$&   $ 1.00$&   $ 0.3950$&   $ 1.25$&   $ 3.5$&   $1.540$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $131$&   $-2.5$&   $ 0.00$&   $ 0.50$&   $ 0.8130$&   $ 1.50$&   $ 9.0$&   $1.540$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $137$&   $-2.0$&   $ 0.50$&   $ 1.00$&   $ 1.9400$&   $ 2.50$&   $11.5$&   $2.520$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 37$&   $-1.0$&   $ 0.50$&   $ 2.50$&   $ 2.6800$&   $ 4.00$&   $ 8.5$&   $2.380$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  1$&   $ 3.0$&   $ 3.00$&   $ 3.00$&   $ 3.0000$&   $ 3.00$&   $ 3.0$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  4$&   $ 2.0$&   $ 4.25$&   $ 8.00$&   $ 7.3800$&   $11.10$&   $11.5$&   $4.640$\tabularnewline
   ~~72&   $  4$&   $ 7.0$&   $ 8.12$&   $10.00$&   $10.4000$&   $12.20$&   $14.5$&   $3.330$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.500$&   $-0.250$&   $ 0.000$&   $ 0.03030$&   $ 0.250$&   $ 1.6200$&   $0.4310$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $263$&   $-1.380$&   $-0.250$&   $ 0.000$&   $ 0.02390$&   $ 0.250$&   $ 1.6200$&   $0.4310$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $318$&   $-1.380$&   $-0.250$&   $ 0.000$&   $ 0.04430$&   $ 0.281$&   $ 1.7500$&   $0.4520$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 44$&   $-0.589$&   $-0.250$&   $ 0.000$&   $-0.03610$&   $ 0.125$&   $ 0.7500$&   $0.3130$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $163$&   $-1.380$&   $-0.250$&   $ 0.000$&   $ 0.05630$&   $ 0.375$&   $ 2.1200$&   $0.4950$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 57$&   $-1.430$&   $ 0.000$&   $ 0.125$&   $ 0.14700$&   $ 0.375$&   $ 1.3800$&   $0.4950$\tabularnewline
   ~~72&   $122$&   $-1.320$&   $-0.125$&   $ 0.125$&   $ 0.16900$&   $ 0.500$&   $ 1.6200$&   $0.5390$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 57$&   $-1.500$&   $-0.125$&   $ 0.125$&   $ 0.19400$&   $ 0.500$&   $ 1.8200$&   $0.6150$\tabularnewline
   ~~96&   $ 47$&   $-1.120$&   $-0.125$&   $ 0.000$&   $ 0.15200$&   $ 0.500$&   $ 1.6200$&   $0.5440$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  2$&   $ 0.375$&   $ 0.406$&   $ 0.438$&   $ 0.43800$&   $ 0.469$&   $ 0.5000$&   $0.0884$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $428$&   $-2.120$&   $-0.375$&   $-0.125$&   $-0.10400$&   $ 0.250$&   $ 1.6200$&   $0.5390$\tabularnewline
   ~~12&   $514$&   $-2.250$&   $-0.375$&   $ 0.000$&   $-0.06990$&   $ 0.250$&   $ 1.6200$&   $0.6010$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $390$&   $-2.880$&   $-0.375$&   $ 0.000$&   $-0.02780$&   $ 0.326$&   $ 2.5000$&   $0.6450$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $318$&   $-2.380$&   $-0.375$&   $-0.125$&   $-0.04430$&   $ 0.375$&   $ 2.5000$&   $0.6370$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $250$&   $-2.500$&   $-0.500$&   $-0.125$&   $-0.09750$&   $ 0.312$&   $ 2.3600$&   $0.7250$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $141$&   $-1.500$&   $-0.375$&   $ 0.000$&   $ 0.02010$&   $ 0.500$&   $ 1.7500$&   $0.5960$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $103$&   $-2.120$&   $-0.375$&   $ 0.000$&   $ 0.02230$&   $ 0.500$&   $ 1.7500$&   $0.7420$\tabularnewline
   ~~84&   $ 95$&   $-2.380$&   $-0.375$&   $-0.125$&   $-0.07280$&   $ 0.250$&   $ 2.0000$&   $0.6580$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 66$&   $-2.500$&   $-0.500$&   $-0.250$&   $-0.19200$&   $ 0.219$&   $ 2.2100$&   $0.7400$\tabularnewline
   ~~108&   $ 21$&   $-1.620$&   $-0.375$&   $ 0.000$&   $-0.00198$&   $ 0.250$&   $ 1.3800$&   $0.6800$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $124$&   $-1.880$&   $-0.406$&   $ 0.000$&   $-0.05920$&   $ 0.375$&   $ 1.7500$&   $0.7250$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $118$&   $-2.000$&   $-0.375$&   $ 0.000$&   $-0.11000$&   $ 0.375$&   $ 2.0000$&   $0.7300$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 28$&   $-1.750$&   $-0.531$&   $-0.268$&   $-0.23900$&   $ 0.125$&   $ 1.0000$&   $0.6130$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  2$&   $-0.875$&   $-0.665$&   $-0.455$&   $-0.45500$&   $-0.246$&   $-0.0357$&   $0.5930$\tabularnewline
   ~~72&   $  1$&   $-0.875$&   $-0.875$&   $-0.875$&   $-0.87500$&   $-0.875$&   $-0.8750$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $263$&   $-1.380$&   $-0.1250$&   $0.000$&   $0.01720$&   $0.125$&   $1.62$&   $0.361$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $257$&   $-1.500$&   $-0.1250$&   $0.000$&   $0.04200$&   $0.250$&   $2.12$&   $0.411$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $305$&   $-1.500$&   $-0.1250$&   $0.000$&   $0.05160$&   $0.250$&   $2.12$&   $0.423$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 41$&   $-1.380$&   $-0.1250$&   $0.000$&   $0.12100$&   $0.300$&   $2.12$&   $0.542$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $155$&   $-1.250$&   $-0.1550$&   $0.000$&   $0.11400$&   $0.250$&   $2.12$&   $0.490$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 54$&   $-0.750$&   $-0.1250$&   $0.000$&   $0.14100$&   $0.250$&   $2.46$&   $0.568$\tabularnewline
   ~~72&   $122$&   $-1.500$&   $-0.1250$&   $0.000$&   $0.20600$&   $0.469$&   $2.25$&   $0.623$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 55$&   $-2.380$&   $ 0.0000$&   $0.125$&   $0.31400$&   $0.625$&   $2.75$&   $0.820$\tabularnewline
   ~~96&   $ 46$&   $-1.380$&   $-0.1250$&   $0.000$&   $0.18800$&   $0.500$&   $2.00$&   $0.566$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  2$&   $ 0.375$&   $ 0.5620$&   $0.750$&   $0.75000$&   $0.938$&   $1.12$&   $0.530$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $424$&   $-1.880$&   $-0.2500$&   $0.000$&   $0.00345$&   $0.375$&   $2.12$&   $0.561$\tabularnewline
   ~~12&   $508$&   $-2.750$&   $-0.2500$&   $0.000$&   $0.01050$&   $0.259$&   $2.25$&   $0.585$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $391$&   $-1.880$&   $-0.2500$&   $0.000$&   $0.10300$&   $0.500$&   $2.12$&   $0.649$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $317$&   $-2.250$&   $-0.2500$&   $0.125$&   $0.15000$&   $0.500$&   $2.14$&   $0.706$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $245$&   $-1.750$&   $-0.2500$&   $0.125$&   $0.22500$&   $0.500$&   $2.88$&   $0.710$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $137$&   $-1.620$&   $-0.1790$&   $0.125$&   $0.27000$&   $0.625$&   $2.50$&   $0.783$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $109$&   $-1.620$&   $-0.2500$&   $0.125$&   $0.20200$&   $0.625$&   $2.29$&   $0.697$\tabularnewline
   ~~84&   $ 99$&   $-1.250$&   $-0.2590$&   $0.125$&   $0.27300$&   $0.812$&   $2.50$&   $0.830$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 67$&   $-2.000$&   $-0.1250$&   $0.250$&   $0.24400$&   $0.625$&   $2.38$&   $0.757$\tabularnewline
   ~~108&   $ 19$&   $-0.750$&   $-0.2500$&   $0.000$&   $0.19600$&   $0.536$&   $1.75$&   $0.696$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $130$&   $-2.750$&   $-0.2500$&   $0.000$&   $0.04210$&   $0.479$&   $1.62$&   $0.616$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $136$&   $-1.620$&   $ 0.0000$&   $0.125$&   $0.21000$&   $0.500$&   $2.12$&   $0.508$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 37$&   $-1.540$&   $-0.1250$&   $0.000$&   $0.11400$&   $0.375$&   $1.50$&   $0.595$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  1$&   $ 0.000$&   $ 0.0000$&   $0.000$&   $0.00000$&   $0.000$&   $0.00$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  4$&   $ 0.000$&   $ 0.0938$&   $0.625$&   $0.84400$&   $1.380$&   $2.12$&   $0.992$\tabularnewline
   ~~72&   $  3$&   $ 0.000$&   $ 0.9110$&   $1.820$&   $1.32000$&   $1.970$&   $2.12$&   $1.150$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.1400$&   $-0.1030$&   $ 0.00000$&   $ 0.01780$&   $ 0.1280$&   $ 0.8210$&   $0.2530$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $263$&   $-0.7510$&   $-0.1030$&   $ 0.00000$&   $ 0.02740$&   $ 0.1280$&   $ 1.4600$&   $0.2510$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $318$&   $-1.3400$&   $-0.1030$&   $ 0.00000$&   $ 0.03000$&   $ 0.1610$&   $ 1.1800$&   $0.3050$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 44$&   $-0.5260$&   $-0.1030$&   $-0.02560$&   $ 0.00677$&   $ 0.1030$&   $ 0.7440$&   $0.2250$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $164$&   $-0.9850$&   $-0.1070$&   $ 0.04180$&   $ 0.04310$&   $ 0.1670$&   $ 1.7200$&   $0.3040$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 57$&   $-0.7250$&   $-0.0466$&   $ 0.13300$&   $ 0.11100$&   $ 0.2210$&   $ 0.7270$&   $0.3140$\tabularnewline
   ~~72&   $122$&   $-1.0100$&   $-0.0229$&   $ 0.10600$&   $ 0.13600$&   $ 0.2640$&   $ 1.3000$&   $0.3290$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 57$&   $-0.7840$&   $-0.0472$&   $ 0.08300$&   $ 0.13100$&   $ 0.2990$&   $ 1.1600$&   $0.3580$\tabularnewline
   ~~96&   $ 47$&   $-1.1100$&   $-0.0128$&   $ 0.08300$&   $ 0.13400$&   $ 0.2190$&   $ 1.5600$&   $0.3950$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  2$&   $ 0.0769$&   $ 0.0904$&   $ 0.10400$&   $ 0.10400$&   $ 0.1170$&   $ 0.1310$&   $0.0381$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $430$&   $-2.0800$&   $-0.2190$&   $-0.02630$&   $-0.03500$&   $ 0.1500$&   $ 1.5900$&   $0.3760$\tabularnewline
   ~~12&   $517$&   $-1.6900$&   $-0.2310$&   $ 0.00000$&   $-0.02020$&   $ 0.1840$&   $ 1.6700$&   $0.3980$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $391$&   $-1.6900$&   $-0.2050$&   $ 0.00000$&   $ 0.02740$&   $ 0.2310$&   $ 1.7400$&   $0.4390$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $314$&   $-1.7300$&   $-0.2050$&   $ 0.02220$&   $ 0.04000$&   $ 0.2920$&   $ 1.9900$&   $0.4530$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $249$&   $-2.3100$&   $-0.2470$&   $ 0.02560$&   $ 0.03160$&   $ 0.3080$&   $ 2.7100$&   $0.5290$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $139$&   $-1.2100$&   $-0.1410$&   $ 0.05130$&   $ 0.07250$&   $ 0.3260$&   $ 1.1300$&   $0.4380$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $103$&   $-1.1300$&   $-0.1650$&   $ 0.05400$&   $ 0.09530$&   $ 0.3850$&   $ 1.4800$&   $0.4670$\tabularnewline
   ~~84&   $ 95$&   $-1.0900$&   $-0.2000$&   $ 0.00540$&   $ 0.01710$&   $ 0.2040$&   $ 1.6000$&   $0.4760$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 66$&   $-1.0900$&   $-0.2760$&   $ 0.00405$&   $ 0.01540$&   $ 0.2060$&   $ 2.5900$&   $0.5200$\tabularnewline
   ~~108&   $ 21$&   $-0.8620$&   $-0.2630$&   $-0.02160$&   $-0.05530$&   $ 0.1500$&   $ 0.7770$&   $0.4130$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $120$&   $-1.6900$&   $-0.2980$&   $ 0.02320$&   $-0.01190$&   $ 0.2840$&   $ 1.5100$&   $0.5540$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $115$&   $-1.3100$&   $-0.3160$&   $-0.00962$&   $ 0.02090$&   $ 0.3150$&   $ 2.1000$&   $0.5420$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 28$&   $-1.4300$&   $-0.2140$&   $ 0.00679$&   $ 0.00151$&   $ 0.4070$&   $ 0.8820$&   $0.4850$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  2$&   $-0.5430$&   $-0.3940$&   $-0.24500$&   $-0.24500$&   $-0.0957$&   $ 0.0535$&   $0.4220$\tabularnewline
   ~~72&   $  1$&   $-0.1910$&   $-0.1910$&   $-0.19100$&   $-0.19100$&   $-0.1910$&   $-0.1910$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $265$&   $-0.879$&   $-0.0513$&   $0.0000$&   $0.00909$&   $0.0769$&   $0.846$&   $0.193$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $257$&   $-1.210$&   $-0.0365$&   $0.0000$&   $0.03900$&   $0.0980$&   $1.620$&   $0.260$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $305$&   $-1.130$&   $-0.0513$&   $0.0000$&   $0.04760$&   $0.1030$&   $2.000$&   $0.284$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 41$&   $-1.330$&   $ 0.0000$&   $0.0513$&   $0.11900$&   $0.2290$&   $2.050$&   $0.469$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $156$&   $-1.050$&   $-0.0516$&   $0.0000$&   $0.08570$&   $0.1290$&   $1.680$&   $0.341$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 54$&   $-0.540$&   $-0.0447$&   $0.0395$&   $0.16500$&   $0.2110$&   $2.540$&   $0.509$\tabularnewline
   ~~72&   $121$&   $-0.994$&   $-0.0513$&   $0.0526$&   $0.16700$&   $0.2660$&   $2.520$&   $0.464$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 55$&   $-1.540$&   $ 0.0000$&   $0.1050$&   $0.25300$&   $0.2600$&   $2.950$&   $0.693$\tabularnewline
   ~~96&   $ 46$&   $-0.994$&   $-0.0444$&   $0.0135$&   $0.06100$&   $0.1450$&   $1.210$&   $0.332$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  2$&   $ 0.158$&   $ 0.2360$&   $0.3150$&   $0.31500$&   $0.3940$&   $0.472$&   $0.222$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $426$&   $-1.460$&   $-0.1670$&   $0.0206$&   $0.05150$&   $0.2540$&   $1.990$&   $0.411$\tabularnewline
   ~~12&   $508$&   $-2.040$&   $-0.1290$&   $0.0428$&   $0.08030$&   $0.2830$&   $2.090$&   $0.459$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $391$&   $-1.410$&   $-0.1050$&   $0.1050$&   $0.18600$&   $0.3930$&   $2.410$&   $0.530$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $316$&   $-2.140$&   $-0.1030$&   $0.1440$&   $0.25400$&   $0.4890$&   $2.510$&   $0.619$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $245$&   $-2.110$&   $-0.1030$&   $0.1540$&   $0.28400$&   $0.5710$&   $2.620$&   $0.648$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $137$&   $-1.050$&   $-0.1030$&   $0.1660$&   $0.32500$&   $0.6910$&   $2.400$&   $0.676$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $109$&   $-1.100$&   $-0.1010$&   $0.1520$&   $0.26500$&   $0.5200$&   $2.250$&   $0.622$\tabularnewline
   ~~84&   $ 99$&   $-1.340$&   $-0.0974$&   $0.1580$&   $0.39500$&   $0.8060$&   $2.400$&   $0.800$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 67$&   $-1.210$&   $-0.0455$&   $0.1320$&   $0.37700$&   $0.5790$&   $2.510$&   $0.772$\tabularnewline
   ~~108&   $ 19$&   $-0.589$&   $-0.1510$&   $0.0850$&   $0.22400$&   $0.7330$&   $1.290$&   $0.564$\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $130$&   $-2.500$&   $-0.1470$&   $0.1260$&   $0.10500$&   $0.4100$&   $1.330$&   $0.524$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $137$&   $-1.460$&   $ 0.1090$&   $0.3160$&   $0.33900$&   $0.5830$&   $1.570$&   $0.458$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $ 37$&   $-0.474$&   $-0.0107$&   $0.3210$&   $0.38000$&   $0.7700$&   $1.890$&   $0.529$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $  1$&   $ 0.718$&   $ 0.7180$&   $0.7180$&   $0.71800$&   $0.7180$&   $0.718$&   $$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $  4$&   $-0.241$&   $ 0.4780$&   $0.7580$&   $0.97900$&   $1.2600$&   $2.640$&   $1.200$\tabularnewline
   ~~72&   $  3$&   $ 0.675$&   $ 0.9730$&   $1.2700$&   $1.54000$&   $1.9700$&   $2.660$&   $1.020$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\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