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=302)	EMCI (N=398)	LMCI (N=655)	AD (N=398)	Combined (N=2271)	Test Statistic
Age [Years]	2278	`69.9/73.2/77.7`	`66.8/70.2/75.7`	`65.9/71.5/76.4`	`69.2/74.3/79.3`	`70.5/75.3/80.3`	`68.2/73.2/78.3`	F=21.9 d.f.=4,2263 P<0.001
Age : (39,49]	2278	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	Chi-square=169 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% ( 125)`	`36% ( 142)`	`21% ( 136)`	`17% ( 66)`	`25% ( 568)`
(69,79]		`61% ( 317)`	`45% ( 137)`	`44% ( 175)`	`49% ( 321)`	`46% ( 185)`	`50% (1135)`
(79,89]		`18% ( 95)`	`10% ( 30)`	`16% ( 64)`	`26% ( 172)`	`31% ( 124)`	`21% ( 485)`
(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	2281	`47% ( 244)`	`38% ( 116)`	`56% ( 223)`	`61% ( 401)`	`56% ( 224)`	`53% (1208)`	Chi-square=54 d.f.=4 P<0.001
Education	2281	`14/16/18`	`16/17/18`	`14/16/18`	`14/16/18`	`13/16/18`	`14/16/18`	F=15.5 d.f.=4,2266 P<0.001
Marital : Divorced	2281	`10% ( 54)`	`13% ( 39)`	`11% ( 43)`	`8% ( 53)`	`4% ( 14)`	`9% ( 203)`	Chi-square=64 d.f.=16 P<0.001
Married		`69% ( 360)`	`72% ( 217)`	`78% ( 309)`	`78% ( 511)`	`84% ( 336)`	`76% (1733)`
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	2281	`0% ( 2)`	`1% ( 2)`	`1% ( 2)`	`0% ( 3)`	`1% ( 3)`	`1% ( 12)`	Chi-square=6.24 d.f.=8 P=0.62
Not Hisp/Latino		`95% ( 494)`	`95% ( 288)`	`94% ( 374)`	`97% ( 634)`	`96% ( 381)`	`96% (2171)`
Hisp/Latino		`4% ( 22)`	`4% ( 12)`	`6% ( 22)`	`3% ( 18)`	`4% ( 14)`	`4% ( 88)`
Race : Am Indian/Alaskan	2281	`0% ( 2)`	`0% ( 0)`	`1% ( 2)`	`0% ( 1)`	`0% ( 0)`	`0% ( 5)`	Chi-square=52.9 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)`	`8% ( 23)`	`3% ( 10)`	`5% ( 30)`	`4% ( 17)`	`5% ( 112)`
White		`91% ( 473)`	`86% ( 259)`	`92% ( 368)`	`93% ( 607)`	`92% ( 367)`	`91% (2074)`
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	2281	`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=2913 d.f.=4,2266 P<0.001
ADAS 13	2258	`6.67/ 9.67/12.67`	`8.33/11.00/14.33`	`9.00/14.00/17.00`	`14.67/18.67/23.33`	`24.67/29.67/35.00`	`10.00/15.00/22.33`	F=667 d.f.=4,2245 P<0.001
MMSE	2281	`29/29/30`	`29/29/30`	`28/29/29`	`26/27/29`	`21/23/25`	`26/28/29`	F=601 d.f.=4,2266 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=299)	EMCI (N=387)	LMCI (N=643)	AD (N=388)	Combined (N=2228)	Test Statistic
Age [Years]	2235	`69.9/73.2/77.7`	`66.8/70.2/75.8`	`66.2/71.5/76.4`	`69.2/74.3/79.2`	`70.4/75.3/80.3`	`68.3/73.2/78.2`	F=21 d.f.=4,2220 P<0.001
Age : (39,49]	2235	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	Chi-square=165 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% ( 124)`	`35% ( 137)`	`21% ( 134)`	`16% ( 64)`	`25% ( 556)`
(69,79]		`61% ( 313)`	`45% ( 135)`	`44% ( 172)`	`49% ( 316)`	`47% ( 181)`	`50% (1117)`
(79,89]		`18% ( 94)`	`10% ( 30)`	`16% ( 62)`	`26% ( 168)`	`31% ( 120)`	`21% ( 474)`
(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	2238	`47% ( 242)`	`38% ( 114)`	`57% ( 219)`	`61% ( 395)`	`56% ( 219)`	`53% (1189)`	Chi-square=55.2 d.f.=4 P<0.001
Education	2238	`14.0/16.0/18.0`	`15.5/17.0/18.0`	`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.=4,2223 P<0.001
Marital : Divorced	2238	`10% ( 53)`	`13% ( 39)`	`11% ( 41)`	`8% ( 53)`	`4% ( 14)`	`9% ( 200)`	Chi-square=63 d.f.=16 P<0.001
Married		`70% ( 357)`	`72% ( 216)`	`78% ( 303)`	`78% ( 501)`	`84% ( 327)`	`76% (1704)`
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	2238	`0% ( 2)`	`1% ( 2)`	`1% ( 2)`	`0% ( 3)`	`1% ( 3)`	`1% ( 12)`	Chi-square=6.5 d.f.=8 P=0.592
Not Hisp/Latino		`95% ( 487)`	`95% ( 285)`	`94% ( 364)`	`97% ( 623)`	`96% ( 372)`	`96% (2131)`
Hisp/Latino		`4% ( 22)`	`4% ( 12)`	`5% ( 21)`	`3% ( 17)`	`3% ( 13)`	`4% ( 85)`
Race : Am Indian/Alaskan	2238	`0% ( 2)`	`0% ( 0)`	`1% ( 2)`	`0% ( 1)`	`0% ( 0)`	`0% ( 5)`	Chi-square=53.3 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)`	`8% ( 23)`	`2% ( 9)`	`5% ( 29)`	`4% ( 17)`	`5% ( 110)`
White		`91% ( 466)`	`86% ( 256)`	`93% ( 359)`	`93% ( 596)`	`92% ( 357)`	`91% (2034)`
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	2238	`0.00/0.00/0.00`	`0.00/0.00/0.00`	`0.50/1.00/1.75`	`1.00/1.50/2.00`	`3.50/4.50/5.00`	`0.00/1.00/2.00`	F=2887 d.f.=4,2223 P<0.001
ADAS 13	2219	`6.67/ 9.67/12.67`	`8.58/11.16/14.33`	`9.00/14.00/17.00`	`14.67/18.84/23.67`	`24.33/29.50/35.00`	`10.00/15.00/22.33`	F=649 d.f.=4,2206 P<0.001
MMSE	2238	`29/29/30`	`29/29/30`	`28/29/29`	`26/27/29`	`21/23/25`	`26/28/29`	F=583 d.f.=4,2223 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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $270$&   $-11.00$&   $-2.00$&   $ 0.00$&   $-0.3850$&   $ 2.00$&   $11.0$&   $ 3.43$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $261$&   $-11.00$&   $-3.00$&   $-0.33$&   $-0.5070$&   $ 2.00$&   $11.0$&   $ 3.74$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $353$&   $-10.00$&   $-2.67$&   $-0.33$&   $-0.3770$&   $ 2.00$&   $13.3$&   $ 3.51$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 44$&   $ -8.00$&   $-2.00$&   $-0.50$&   $-0.2420$&   $ 2.00$&   $11.0$&   $ 3.68$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $161$&   $ -8.00$&   $-2.00$&   $ 1.67$&   $ 1.3600$&   $ 4.00$&   $15.0$&   $ 4.63$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 53$&   $ -1.67$&   $ 2.67$&   $ 4.33$&   $ 5.1500$&   $ 7.00$&   $18.0$&   $ 4.47$\tabularnewline
   ~~72&   $119$&   $ -2.67$&   $ 2.00$&   $ 4.67$&   $ 5.4700$&   $ 7.67$&   $23.7$&   $ 4.65$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 53$&   $ -4.33$&   $ 3.33$&   $ 6.00$&   $ 7.0800$&   $ 8.67$&   $28.3$&   $ 6.36$\tabularnewline
   ~~96&   $ 44$&   $ -5.33$&   $ 2.00$&   $ 5.16$&   $ 5.6100$&   $ 7.83$&   $23.0$&   $ 5.49$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  3$&   $  5.00$&   $ 5.66$&   $ 6.33$&   $ 8.1100$&   $ 9.66$&   $13.0$&   $ 4.29$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $429$&   $-12.00$&   $-3.00$&   $ 0.00$&   $ 0.0583$&   $ 3.00$&   $16.0$&   $ 4.38$\tabularnewline
   ~~12&   $514$&   $-15.00$&   $-3.00$&   $-0.50$&   $ 0.0745$&   $ 3.00$&   $54.0$&   $ 5.02$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $394$&   $-11.00$&   $-2.58$&   $ 0.00$&   $ 1.1300$&   $ 4.00$&   $21.0$&   $ 5.49$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $317$&   $-14.00$&   $-2.00$&   $ 1.00$&   $ 2.0600$&   $ 5.00$&   $49.0$&   $ 7.45$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $252$&   $-12.00$&   $-2.00$&   $ 1.00$&   $ 3.4800$&   $ 6.00$&   $55.0$&   $ 9.57$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $139$&   $ -7.00$&   $ 0.00$&   $ 3.00$&   $ 5.5000$&   $ 8.16$&   $71.0$&   $10.90$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $101$&   $ -5.00$&   $ 2.00$&   $ 4.67$&   $ 5.7600$&   $ 8.00$&   $37.0$&   $ 6.79$\tabularnewline
   ~~84&   $ 88$&   $ -3.33$&   $ 2.67$&   $ 5.34$&   $ 6.8900$&   $ 9.42$&   $24.7$&   $ 6.24$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 64$&   $ -5.00$&   $ 3.25$&   $ 6.00$&   $ 8.0700$&   $11.40$&   $38.7$&   $ 7.75$\tabularnewline
   ~~108&   $ 21$&   $ -5.67$&   $ 3.00$&   $ 5.33$&   $ 6.4400$&   $ 8.33$&   $25.0$&   $ 6.86$\tabularnewline
\rowcolor[gray]{.9}   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $127$&   $-12.00$&   $-1.50$&   $ 2.00$&   $ 2.3800$&   $ 6.50$&   $23.0$&   $ 5.62$\tabularnewline
   ~~12&   $129$&   $-13.00$&   $ 0.33$&   $ 3.67$&   $ 4.6800$&   $ 8.00$&   $27.0$&   $ 6.36$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 37$&   $ -5.00$&   $ 3.00$&   $ 7.00$&   $ 8.5900$&   $13.00$&   $36.0$&   $ 9.19$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  1$&   $  8.00$&   $ 8.00$&   $ 8.00$&   $ 8.0000$&   $ 8.00$&   $ 8.0$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  2$&   $  6.33$&   $ 7.41$&   $ 8.50$&   $ 8.5000$&   $ 9.59$&   $10.7$&   $ 3.07$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  1$&   $ 10.00$&   $10.00$&   $10.00$&   $10.0000$&   $10.00$&   $10.0$&   $$\tabularnewline
   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $274$&   $ -4$&   $-1.00$&   $ 0.0$&   $-0.0547$&   $ 1.0$&   $ 4$&   $1.40$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $264$&   $ -8$&   $-1.00$&   $ 0.0$&   $-0.2120$&   $ 1.0$&   $ 4$&   $1.59$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $360$&   $ -5$&   $-1.00$&   $ 0.0$&   $-0.1250$&   $ 1.0$&   $ 4$&   $1.44$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 47$&   $ -5$&   $-1.00$&   $ 0.0$&   $-0.3830$&   $ 1.0$&   $ 4$&   $1.80$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $161$&   $ -7$&   $-1.00$&   $ 0.0$&   $-0.2730$&   $ 1.0$&   $ 4$&   $1.69$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 53$&   $-10$&   $-1.00$&   $ 0.0$&   $-0.1890$&   $ 0.0$&   $ 4$&   $1.97$\tabularnewline
   ~~72&   $118$&   $ -8$&   $-1.00$&   $ 0.0$&   $-0.3310$&   $ 1.0$&   $ 4$&   $1.91$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 52$&   $ -7$&   $-2.25$&   $ 0.0$&   $-1.0400$&   $ 0.0$&   $ 3$&   $1.96$\tabularnewline
   ~~96&   $ 45$&   $ -4$&   $-2.00$&   $ 0.0$&   $-0.3780$&   $ 1.0$&   $ 4$&   $1.68$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  3$&   $ -3$&   $-2.50$&   $-2.0$&   $-1.3300$&   $-0.5$&   $ 1$&   $2.08$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $430$&   $-10$&   $-2.00$&   $ 0.0$&   $-0.4490$&   $ 1.0$&   $ 5$&   $1.88$\tabularnewline
   ~~12&   $518$&   $-11$&   $-2.00$&   $ 0.0$&   $-0.5170$&   $ 1.0$&   $ 6$&   $2.08$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $400$&   $-11$&   $-2.00$&   $ 0.0$&   $-0.9000$&   $ 1.0$&   $ 6$&   $2.45$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $318$&   $-23$&   $-2.00$&   $-1.0$&   $-1.2400$&   $ 1.0$&   $ 6$&   $3.32$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $256$&   $-20$&   $-3.00$&   $-1.0$&   $-1.6000$&   $ 1.0$&   $ 5$&   $3.82$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $143$&   $-30$&   $-3.00$&   $-1.0$&   $-1.9900$&   $ 0.0$&   $ 4$&   $4.64$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $105$&   $-24$&   $-2.00$&   $ 0.0$&   $-1.5300$&   $ 1.0$&   $ 5$&   $4.23$\tabularnewline
   ~~84&   $ 93$&   $-20$&   $-3.00$&   $-1.0$&   $-1.7300$&   $ 1.0$&   $ 6$&   $4.30$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 65$&   $-12$&   $-2.00$&   $-1.0$&   $-1.6300$&   $ 1.0$&   $ 5$&   $3.68$\tabularnewline
   ~~108&   $ 22$&   $ -5$&   $-1.75$&   $-0.5$&   $-0.7730$&   $ 1.0$&   $ 2$&   $2.00$\tabularnewline
\rowcolor[gray]{.9}   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $131$&   $-16$&   $-3.00$&   $-1.0$&   $-1.1800$&   $ 1.0$&   $ 8$&   $3.07$\tabularnewline
   ~~12&   $134$&   $-19$&   $-4.75$&   $-2.0$&   $-2.5100$&   $ 0.0$&   $ 5$&   $4.13$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 39$&   $-15$&   $-6.00$&   $-4.0$&   $-4.2300$&   $-2.0$&   $ 3$&   $3.95$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  1$&   $ -2$&   $-2.00$&   $-2.0$&   $-2.0000$&   $-2.0$&   $-2$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  2$&   $ -4$&   $-3.00$&   $-2.0$&   $-2.0000$&   $-1.0$&   $ 0$&   $2.83$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  2$&   $ -5$&   $-4.50$&   $-4.0$&   $-4.0000$&   $-3.5$&   $-3$&   $1.41$\tabularnewline
   ~~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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.0$&   $ 0.000$&   $ 0.00$&   $ 0.0879$&   $ 0.000$&   $ 2.5$&   $0.348$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $262$&   $-1.0$&   $ 0.000$&   $ 0.00$&   $ 0.1280$&   $ 0.000$&   $ 4.0$&   $0.495$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $371$&   $-1.0$&   $ 0.000$&   $ 0.00$&   $ 0.1580$&   $ 0.000$&   $ 5.0$&   $0.574$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 44$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.5340$&   $ 0.500$&   $ 5.0$&   $1.200$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $156$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.2020$&   $ 0.000$&   $ 5.0$&   $0.686$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 56$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.5540$&   $ 0.500$&   $11.0$&   $1.710$\tabularnewline
   ~~72&   $123$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.4270$&   $ 0.250$&   $10.0$&   $1.240$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 60$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.8250$&   $ 0.625$&   $12.0$&   $2.000$\tabularnewline
   ~~96&   $ 47$&   $-0.5$&   $ 0.000$&   $ 0.00$&   $ 0.7340$&   $ 0.500$&   $15.5$&   $2.370$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  4$&   $ 0.0$&   $ 0.000$&   $ 0.25$&   $ 0.3750$&   $ 0.625$&   $ 1.0$&   $0.479$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $426$&   $-3.5$&   $-0.500$&   $ 0.00$&   $ 0.1310$&   $ 0.500$&   $ 3.0$&   $0.807$\tabularnewline
   ~~12&   $516$&   $-3.0$&   $-0.500$&   $ 0.00$&   $ 0.1950$&   $ 0.500$&   $ 5.5$&   $1.020$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $411$&   $-3.0$&   $-0.500$&   $ 0.00$&   $ 0.5950$&   $ 1.000$&   $11.5$&   $1.660$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $328$&   $-3.5$&   $-0.500$&   $ 0.00$&   $ 0.9020$&   $ 1.500$&   $12.5$&   $2.370$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $257$&   $-3.5$&   $-0.500$&   $ 0.00$&   $ 1.1200$&   $ 2.000$&   $16.0$&   $2.910$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $141$&   $-3.0$&   $-0.500$&   $ 0.00$&   $ 0.9260$&   $ 1.500$&   $14.5$&   $2.650$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $109$&   $-3.0$&   $-0.500$&   $ 0.00$&   $ 1.2200$&   $ 1.500$&   $15.5$&   $3.430$\tabularnewline
   ~~84&   $ 96$&   $-3.5$&   $-0.500$&   $ 0.25$&   $ 1.4400$&   $ 1.620$&   $15.0$&   $3.520$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 74$&   $-3.5$&   $-0.500$&   $ 0.00$&   $ 1.4400$&   $ 1.500$&   $14.0$&   $3.620$\tabularnewline
   ~~108&   $ 29$&   $-2.5$&   $-1.000$&   $ 0.00$&   $ 1.3800$&   $ 1.500$&   $16.5$&   $3.960$\tabularnewline
\rowcolor[gray]{.9}   ~~120&   $  2$&   $-0.5$&   $-0.500$&   $-0.50$&   $-0.5000$&   $-0.500$&   $-0.5$&   $0.000$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $131$&   $-2.5$&   $ 0.000$&   $ 0.50$&   $ 0.8130$&   $ 1.500$&   $ 9.0$&   $1.540$\tabularnewline
   ~~12&   $141$&   $-2.0$&   $ 0.000$&   $ 1.00$&   $ 1.8800$&   $ 2.500$&   $11.5$&   $2.500$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 40$&   $-1.0$&   $ 0.875$&   $ 2.25$&   $ 2.7500$&   $ 4.120$&   $ 8.5$&   $2.490$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  1$&   $ 2.0$&   $ 2.000$&   $ 2.00$&   $ 2.0000$&   $ 2.000$&   $ 2.0$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  1$&   $ 3.0$&   $ 3.000$&   $ 3.00$&   $ 3.0000$&   $ 3.000$&   $ 3.0$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  4$&   $ 2.0$&   $ 4.250$&   $ 8.00$&   $ 7.3800$&   $11.100$&   $11.5$&   $4.640$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  4$&   $ 7.0$&   $ 8.120$&   $10.00$&   $10.4000$&   $12.200$&   $14.5$&   $3.330$\tabularnewline
   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.500$&   $-0.2500$&   $ 0.0000$&   $ 0.0303$&   $ 0.250$&   $ 1.6200$&   $0.431$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $265$&   $-1.380$&   $-0.2500$&   $ 0.0000$&   $ 0.0214$&   $ 0.250$&   $ 1.6200$&   $0.426$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $386$&   $-2.000$&   $-0.2500$&   $ 0.0000$&   $ 0.0177$&   $ 0.250$&   $ 1.7500$&   $0.448$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 45$&   $-0.589$&   $-0.2500$&   $ 0.0000$&   $-0.0381$&   $ 0.125$&   $ 0.7500$&   $0.310$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $163$&   $-1.380$&   $-0.2500$&   $ 0.0000$&   $ 0.0563$&   $ 0.375$&   $ 2.1200$&   $0.495$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 57$&   $-1.430$&   $ 0.0000$&   $ 0.1250$&   $ 0.1460$&   $ 0.375$&   $ 1.3800$&   $0.494$\tabularnewline
   ~~72&   $122$&   $-1.320$&   $-0.1250$&   $ 0.1250$&   $ 0.1690$&   $ 0.500$&   $ 1.6200$&   $0.539$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 61$&   $-1.500$&   $-0.1250$&   $ 0.1250$&   $ 0.1970$&   $ 0.500$&   $ 1.8200$&   $0.615$\tabularnewline
   ~~96&   $ 50$&   $-1.120$&   $-0.1250$&   $ 0.0625$&   $ 0.2010$&   $ 0.500$&   $ 2.2500$&   $0.609$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  4$&   $-0.500$&   $ 0.0625$&   $ 0.3120$&   $ 0.1560$&   $ 0.406$&   $ 0.5000$&   $0.449$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $428$&   $-2.120$&   $-0.3750$&   $-0.1250$&   $-0.1040$&   $ 0.250$&   $ 1.6200$&   $0.539$\tabularnewline
   ~~12&   $520$&   $-2.250$&   $-0.3750$&   $ 0.0000$&   $-0.0670$&   $ 0.250$&   $ 1.6200$&   $0.599$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $410$&   $-2.880$&   $-0.3750$&   $ 0.0000$&   $-0.0268$&   $ 0.326$&   $ 2.5000$&   $0.642$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $321$&   $-2.380$&   $-0.3750$&   $-0.0893$&   $-0.0427$&   $ 0.375$&   $ 2.5000$&   $0.634$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $250$&   $-2.500$&   $-0.5000$&   $-0.1250$&   $-0.0975$&   $ 0.312$&   $ 2.3600$&   $0.725$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $141$&   $-1.500$&   $-0.3750$&   $ 0.0000$&   $ 0.0201$&   $ 0.500$&   $ 1.7500$&   $0.596$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $103$&   $-2.120$&   $-0.3750$&   $ 0.0000$&   $ 0.0223$&   $ 0.500$&   $ 1.7500$&   $0.742$\tabularnewline
   ~~84&   $ 95$&   $-2.380$&   $-0.3750$&   $-0.1250$&   $-0.0728$&   $ 0.250$&   $ 2.0000$&   $0.658$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 72$&   $-2.500$&   $-0.5000$&   $-0.2500$&   $-0.1860$&   $ 0.250$&   $ 2.2100$&   $0.724$\tabularnewline
   ~~108&   $ 27$&   $-2.250$&   $-0.5000$&   $-0.1250$&   $-0.1770$&   $ 0.125$&   $ 1.3800$&   $0.772$\tabularnewline
\rowcolor[gray]{.9}   ~~120&   $  1$&   $-0.250$&   $-0.2500$&   $-0.2500$&   $-0.2500$&   $-0.250$&   $-0.2500$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $124$&   $-1.880$&   $-0.4060$&   $ 0.0000$&   $-0.0592$&   $ 0.375$&   $ 1.7500$&   $0.725$\tabularnewline
   ~~12&   $121$&   $-2.000$&   $-0.3750$&   $ 0.0000$&   $-0.1200$&   $ 0.375$&   $ 2.0000$&   $0.736$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 30$&   $-1.750$&   $-0.5000$&   $-0.2500$&   $-0.1480$&   $ 0.125$&   $ 2.1200$&   $0.734$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  1$&   $-0.500$&   $-0.5000$&   $-0.5000$&   $-0.5000$&   $-0.500$&   $-0.5000$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  2$&   $-0.875$&   $-0.6650$&   $-0.4550$&   $-0.4550$&   $-0.246$&   $-0.0357$&   $0.593$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  1$&   $-0.875$&   $-0.8750$&   $-0.8750$&   $-0.8750$&   $-0.875$&   $-0.8750$&   $$\tabularnewline
   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $263$&   $-1.380$&   $-0.1250$&   $0.000$&   $0.01720$&   $0.125$&   $1.62$&   $0.361$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $259$&   $-1.500$&   $-0.1250$&   $0.000$&   $0.04410$&   $0.250$&   $2.12$&   $0.409$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $364$&   $-1.500$&   $-0.1250$&   $0.000$&   $0.05120$&   $0.250$&   $2.12$&   $0.409$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 43$&   $-1.380$&   $-0.1250$&   $0.125$&   $0.17100$&   $0.338$&   $2.12$&   $0.611$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $155$&   $-1.250$&   $-0.1550$&   $0.000$&   $0.11400$&   $0.250$&   $2.12$&   $0.490$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 54$&   $-0.750$&   $-0.1250$&   $0.000$&   $0.14100$&   $0.250$&   $2.46$&   $0.568$\tabularnewline
   ~~72&   $122$&   $-1.500$&   $-0.1250$&   $0.000$&   $0.20600$&   $0.469$&   $2.25$&   $0.623$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 60$&   $-2.380$&   $-0.0312$&   $0.134$&   $0.34400$&   $0.625$&   $2.75$&   $0.859$\tabularnewline
   ~~96&   $ 47$&   $-1.380$&   $-0.1250$&   $0.000$&   $0.17800$&   $0.500$&   $2.00$&   $0.563$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  4$&   $-0.125$&   $ 0.2500$&   $0.500$&   $0.50000$&   $0.750$&   $1.12$&   $0.520$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $424$&   $-1.880$&   $-0.2500$&   $0.000$&   $0.00345$&   $0.375$&   $2.12$&   $0.561$\tabularnewline
   ~~12&   $514$&   $-2.750$&   $-0.2500$&   $0.000$&   $0.01110$&   $0.286$&   $2.25$&   $0.585$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $409$&   $-1.880$&   $-0.2500$&   $0.000$&   $0.09790$&   $0.500$&   $2.12$&   $0.647$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $320$&   $-2.250$&   $-0.2500$&   $0.125$&   $0.15400$&   $0.500$&   $2.14$&   $0.707$\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&   $ 73$&   $-2.000$&   $-0.1250$&   $0.250$&   $0.26300$&   $0.625$&   $2.38$&   $0.778$\tabularnewline
   ~~108&   $ 27$&   $-0.750$&   $-0.2500$&   $0.000$&   $0.26800$&   $0.688$&   $2.50$&   $0.770$\tabularnewline
\rowcolor[gray]{.9}   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $130$&   $-2.750$&   $-0.2500$&   $0.000$&   $0.04210$&   $0.479$&   $1.62$&   $0.616$\tabularnewline
   ~~12&   $139$&   $-1.620$&   $ 0.0000$&   $0.125$&   $0.21500$&   $0.500$&   $2.12$&   $0.507$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 40$&   $-1.540$&   $-0.1250$&   $0.000$&   $0.13100$&   $0.375$&   $1.50$&   $0.581$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  1$&   $ 1.250$&   $ 1.2500$&   $1.250$&   $1.25000$&   $1.250$&   $1.25$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  1$&   $ 0.000$&   $ 0.0000$&   $0.000$&   $0.00000$&   $0.000$&   $0.00$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  4$&   $ 0.000$&   $ 0.0938$&   $0.625$&   $0.84400$&   $1.380$&   $2.12$&   $0.992$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  4$&   $ 0.000$&   $ 0.8440$&   $1.470$&   $1.27000$&   $1.900$&   $2.12$&   $0.943$\tabularnewline
   ~~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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.140$&   $-0.103000$&   $ 0.00000$&   $ 0.01780$&   $ 0.1280$&   $ 0.8210$&   $0.253$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $265$&   $-0.751$&   $-0.103000$&   $ 0.00000$&   $ 0.02540$&   $ 0.1280$&   $ 1.4600$&   $0.247$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $386$&   $-1.340$&   $-0.103000$&   $ 0.00000$&   $ 0.01400$&   $ 0.1320$&   $ 1.1800$&   $0.298$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 45$&   $-0.526$&   $-0.103000$&   $-0.02560$&   $ 0.00603$&   $ 0.1030$&   $ 0.7440$&   $0.223$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $164$&   $-0.985$&   $-0.107000$&   $ 0.04180$&   $ 0.04310$&   $ 0.1670$&   $ 1.7200$&   $0.304$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 57$&   $-0.725$&   $-0.046600$&   $ 0.13300$&   $ 0.11200$&   $ 0.2210$&   $ 0.7270$&   $0.314$\tabularnewline
   ~~72&   $122$&   $-1.010$&   $-0.022900$&   $ 0.10600$&   $ 0.13600$&   $ 0.2640$&   $ 1.3000$&   $0.329$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 61$&   $-0.784$&   $-0.051200$&   $ 0.08300$&   $ 0.13700$&   $ 0.3100$&   $ 1.1600$&   $0.363$\tabularnewline
   ~~96&   $ 50$&   $-1.110$&   $ 0.000675$&   $ 0.08570$&   $ 0.18400$&   $ 0.2200$&   $ 2.6400$&   $0.522$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  4$&   $-0.147$&   $ 0.020800$&   $ 0.10400$&   $ 0.12600$&   $ 0.2090$&   $ 0.4420$&   $0.243$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $430$&   $-2.080$&   $-0.219000$&   $-0.02630$&   $-0.03500$&   $ 0.1500$&   $ 1.5900$&   $0.376$\tabularnewline
   ~~12&   $523$&   $-1.690$&   $-0.234000$&   $ 0.00000$&   $-0.01990$&   $ 0.1860$&   $ 1.6700$&   $0.396$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $411$&   $-1.690$&   $-0.205000$&   $ 0.00000$&   $ 0.02440$&   $ 0.2310$&   $ 1.7400$&   $0.441$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $317$&   $-1.730$&   $-0.205000$&   $ 0.02560$&   $ 0.04220$&   $ 0.3030$&   $ 1.9900$&   $0.452$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $249$&   $-2.310$&   $-0.247000$&   $ 0.02560$&   $ 0.03160$&   $ 0.3080$&   $ 2.7100$&   $0.529$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $139$&   $-1.210$&   $-0.141000$&   $ 0.05130$&   $ 0.07250$&   $ 0.3260$&   $ 1.1300$&   $0.438$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $103$&   $-1.130$&   $-0.165000$&   $ 0.05400$&   $ 0.09530$&   $ 0.3850$&   $ 1.4800$&   $0.467$\tabularnewline
   ~~84&   $ 95$&   $-1.090$&   $-0.200000$&   $ 0.00540$&   $ 0.01710$&   $ 0.2040$&   $ 1.6000$&   $0.476$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 72$&   $-1.090$&   $-0.253000$&   $ 0.00405$&   $ 0.02130$&   $ 0.1840$&   $ 2.5900$&   $0.510$\tabularnewline
   ~~108&   $ 27$&   $-0.862$&   $-0.387000$&   $-0.07020$&   $-0.09200$&   $ 0.1310$&   $ 0.7770$&   $0.424$\tabularnewline
\rowcolor[gray]{.9}   ~~120&   $  1$&   $-0.395$&   $-0.395000$&   $-0.39500$&   $-0.39500$&   $-0.3950$&   $-0.3950$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $120$&   $-1.690$&   $-0.298000$&   $ 0.02320$&   $-0.01190$&   $ 0.2840$&   $ 1.5100$&   $0.554$\tabularnewline
   ~~12&   $118$&   $-1.380$&   $-0.347000$&   $-0.01060$&   $ 0.00649$&   $ 0.2950$&   $ 2.1000$&   $0.551$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 30$&   $-1.430$&   $-0.168000$&   $ 0.05810$&   $ 0.08140$&   $ 0.4090$&   $ 2.3200$&   $0.631$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  1$&   $ 0.553$&   $ 0.553000$&   $ 0.55300$&   $ 0.55300$&   $ 0.5530$&   $ 0.5530$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  2$&   $-0.543$&   $-0.394000$&   $-0.24500$&   $-0.24500$&   $-0.0957$&   $ 0.0535$&   $0.422$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  1$&   $-0.191$&   $-0.191000$&   $-0.19100$&   $-0.19100$&   $-0.1910$&   $-0.1910$&   $$\tabularnewline
   ~~84&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $265$&   $-0.8790$&   $-0.05130$&   $0.000000$&   $0.00909$&   $0.0769$&   $0.846$&   $0.193$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $259$&   $-1.2100$&   $-0.02880$&   $0.000000$&   $0.04080$&   $0.0988$&   $1.620$&   $0.258$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $364$&   $-1.1300$&   $-0.05130$&   $0.000000$&   $0.04160$&   $0.1030$&   $2.000$&   $0.269$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 43$&   $-1.3300$&   $ 0.00000$&   $0.051300$&   $0.14100$&   $0.2400$&   $2.050$&   $0.483$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $156$&   $-1.0500$&   $-0.05160$&   $0.000000$&   $0.08570$&   $0.1290$&   $1.680$&   $0.341$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 54$&   $-0.5400$&   $-0.04470$&   $0.039500$&   $0.16500$&   $0.2110$&   $2.540$&   $0.509$\tabularnewline
   ~~72&   $121$&   $-0.9940$&   $-0.05130$&   $0.052600$&   $0.16700$&   $0.2660$&   $2.520$&   $0.464$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 60$&   $-1.5400$&   $-0.01280$&   $0.105000$&   $0.29300$&   $0.3190$&   $2.950$&   $0.734$\tabularnewline
   ~~96&   $ 47$&   $-0.9940$&   $-0.05090$&   $0.000675$&   $0.05810$&   $0.1330$&   $1.210$&   $0.329$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  4$&   $-0.0301$&   $ 0.11100$&   $0.251000$&   $0.23600$&   $0.3760$&   $0.472$&   $0.219$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $426$&   $-1.4600$&   $-0.16700$&   $0.020600$&   $0.05150$&   $0.2540$&   $1.990$&   $0.411$\tabularnewline
   ~~12&   $514$&   $-2.0400$&   $-0.13100$&   $0.047200$&   $0.08040$&   $0.2820$&   $2.090$&   $0.458$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $410$&   $-1.4100$&   $-0.11400$&   $0.107000$&   $0.18400$&   $0.3970$&   $2.410$&   $0.530$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $319$&   $-2.1400$&   $-0.10100$&   $0.133000$&   $0.25500$&   $0.4900$&   $2.510$&   $0.617$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $245$&   $-2.1100$&   $-0.10300$&   $0.154000$&   $0.28400$&   $0.5710$&   $2.620$&   $0.648$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $137$&   $-1.0500$&   $-0.10300$&   $0.166000$&   $0.32500$&   $0.6910$&   $2.400$&   $0.676$\tabularnewline
   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $109$&   $-1.1000$&   $-0.10100$&   $0.152000$&   $0.26500$&   $0.5200$&   $2.250$&   $0.622$\tabularnewline
   ~~84&   $ 99$&   $-1.3400$&   $-0.09740$&   $0.158000$&   $0.39500$&   $0.8060$&   $2.400$&   $0.800$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~96&   $ 73$&   $-1.2100$&   $-0.04860$&   $0.131000$&   $0.40100$&   $0.5790$&   $2.510$&   $0.797$\tabularnewline
   ~~108&   $ 27$&   $-0.5890$&   $-0.09010$&   $0.086300$&   $0.39400$&   $0.9030$&   $2.820$&   $0.746$\tabularnewline
\rowcolor[gray]{.9}   ~~120&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $130$&   $-2.5000$&   $-0.14700$&   $0.126000$&   $0.10500$&   $0.4100$&   $1.330$&   $0.524$\tabularnewline
   ~~12&   $140$&   $-1.4600$&   $ 0.10800$&   $0.316000$&   $0.33700$&   $0.5860$&   $1.570$&   $0.456$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 40$&   $-0.4740$&   $ 0.00461$&   $0.340000$&   $0.39500$&   $0.7720$&   $1.890$&   $0.519$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  1$&   $ 1.1100$&   $ 1.11000$&   $1.110000$&   $1.11000$&   $1.1100$&   $1.110$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  1$&   $ 0.7180$&   $ 0.71800$&   $0.718000$&   $0.71800$&   $0.7180$&   $0.718$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  4$&   $-0.2410$&   $ 0.47800$&   $0.758000$&   $0.97900$&   $1.2600$&   $2.640$&   $1.200$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  4$&   $ 0.6750$&   $ 1.01000$&   $1.200000$&   $1.43000$&   $1.6200$&   $2.660$&   $0.858$\tabularnewline
   ~~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