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=513)	SMC (N=288)	EMCI (N=368)	LMCI (N=631)	AD (N=377)	Combined (N=2177)	Test Statistic
Age [Years]	2199	`70.0/73.2/77.7`	`66.9/70.3/75.7`	`65.5/71.2/76.5`	`69.3/74.3/79.3`	`70.7/75.3/80.3`	`68.3/73.3/78.3`	F=20.9 d.f.=4,2170 P<0.001
Age : (39,49]	2198	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	Chi-square=167 d.f.=16 P<0.001
(49,59]		`1% ( 4)`	`2% ( 6)`	`5% ( 17)`	`3% ( 21)`	`4% ( 15)`	`3% ( 63)`
(59,69]		`19% ( 96)`	`40% ( 115)`	`36% ( 134)`	`21% ( 131)`	`16% ( 62)`	`25% ( 538)`
(69,79]		`62% ( 316)`	`47% ( 134)`	`42% ( 155)`	`49% ( 307)`	`47% ( 177)`	`50% (1089)`
(79,89]		`19% ( 95)`	`10% ( 28)`	`17% ( 62)`	`27% ( 169)`	`31% ( 116)`	`22% ( 470)`
(89,99]		`0% ( 1)`	`1% ( 4)`	`0% ( 0)`	`0% ( 2)`	`2% ( 7)`	`1% ( 14)`
(99,109]		`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`
Sex : Male	2201	`48% ( 244)`	`39% ( 113)`	`56% ( 205)`	`61% ( 386)`	`56% ( 211)`	`53% (1159)`	Chi-square=47.3 d.f.=4 P<0.001
Education	2201	`14.0/16.0/18.0`	`15.8/17.0/18.0`	`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=14.8 d.f.=4,2172 P<0.001
Marital : Divorced	2201	`10% ( 53)`	`12% ( 35)`	`11% ( 42)`	`8% ( 51)`	`4% ( 14)`	`9% ( 195)`	Chi-square=58.7 d.f.=16 P<0.001
Married		`69% ( 356)`	`72% ( 208)`	`76% ( 281)`	`78% ( 492)`	`84% ( 315)`	`76% (1652)`
Never married		`5% ( 27)`	`5% ( 14)`	`4% ( 16)`	`2% ( 11)`	`3% ( 10)`	`4% ( 78)`
Unknown		`0% ( 1)`	`0% ( 1)`	`1% ( 4)`	`0% ( 2)`	`0% ( 0)`	`0% ( 8)`
Widowed		`15% ( 76)`	`10% ( 30)`	`7% ( 25)`	`12% ( 75)`	`10% ( 38)`	`11% ( 244)`
Ethnicity : Unknown	2201	`0% ( 2)`	`1% ( 2)`	`1% ( 2)`	`0% ( 3)`	`1% ( 3)`	`1% ( 12)`	Chi-square=4.32 d.f.=8 P=0.828
Not Hisp/Latino		`96% ( 494)`	`95% ( 275)`	`95% ( 348)`	`97% ( 611)`	`96% ( 361)`	`96% (2089)`
Hisp/Latino		`3% ( 17)`	`4% ( 11)`	`5% ( 18)`	`3% ( 17)`	`3% ( 13)`	`3% ( 76)`
Race : Am Indian/Alaskan	2201	`0% ( 2)`	`0% ( 0)`	`0% ( 1)`	`0% ( 1)`	`0% ( 0)`	`0% ( 4)`	Chi-square=48.7 d.f.=24 P=0.002
Asian		`2% ( 9)`	`3% ( 9)`	`1% ( 4)`	`2% ( 12)`	`2% ( 8)`	`2% ( 42)`
Hawaiian/Other PI		`0% ( 0)`	`0% ( 0)`	`0% ( 1)`	`0% ( 1)`	`0% ( 0)`	`0% ( 2)`
Black		`6% ( 32)`	`5% ( 13)`	`2% ( 9)`	`4% ( 26)`	`4% ( 14)`	`4% ( 94)`
White		`91% ( 468)`	`89% ( 255)`	`93% ( 342)`	`93% ( 588)`	`93% ( 351)`	`92% (2004)`
More than one		`0% ( 2)`	`3% ( 10)`	`2% ( 8)`	`0% ( 3)`	`1% ( 4)`	`1% ( 27)`
Unknown		`0% ( 0)`	`0% ( 1)`	`1% ( 3)`	`0% ( 0)`	`0% ( 0)`	`0% ( 4)`
CDR-SB	2201	`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=2972 d.f.=4,2172 P<0.001
ADAS 13	2174	`6.67/ 9.33/12.67`	`8.00/11.00/14.33`	`9.00/13.00/17.00`	`14.67/18.67/23.33`	`24.59/29.67/35.00`	`10.00/15.00/22.00`	F=648 d.f.=4,2151 P<0.001
MMSE	2201	`29/29/30`	`29/29/30`	`28/29/29`	`26/27/29`	`21/23/25`	`26/28/29`	F=589 d.f.=4,2172 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=506)	SMC (N=285)	EMCI (N=357)	LMCI (N=619)	AD (N=367)	Combined (N=2134)	Test Statistic
Age [Years]	2156	`70.0/73.2/77.7`	`66.9/70.3/75.8`	`65.8/71.3/76.5`	`69.3/74.3/79.3`	`70.7/75.3/80.3`	`68.3/73.2/78.3`	F=20 d.f.=4,2127 P<0.001
Age : (39,49]	2155	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	Chi-square=162 d.f.=16 P<0.001
(49,59]		`1% ( 4)`	`2% ( 6)`	`4% ( 16)`	`3% ( 20)`	`4% ( 15)`	`3% ( 61)`
(59,69]		`19% ( 94)`	`40% ( 114)`	`36% ( 129)`	`21% ( 129)`	`16% ( 60)`	`25% ( 526)`
(69,79]		`62% ( 312)`	`46% ( 132)`	`43% ( 152)`	`49% ( 302)`	`47% ( 173)`	`50% (1071)`
(79,89]		`19% ( 94)`	`10% ( 28)`	`17% ( 60)`	`27% ( 165)`	`31% ( 112)`	`22% ( 459)`
(89,99]		`0% ( 1)`	`1% ( 4)`	`0% ( 0)`	`0% ( 2)`	`2% ( 7)`	`1% ( 14)`
(99,109]		`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`	`0% ( 0)`
Sex : Male	2158	`48% ( 242)`	`39% ( 111)`	`56% ( 201)`	`61% ( 380)`	`56% ( 206)`	`53% (1140)`	Chi-square=48.4 d.f.=4 P<0.001
Education	2158	`14/16/18`	`15/17/18`	`14/16/18`	`14/16/18`	`13/16/18`	`14/16/18`	F=14.3 d.f.=4,2129 P<0.001
Marital : Divorced	2158	`10% ( 52)`	`12% ( 35)`	`11% ( 40)`	`8% ( 51)`	`4% ( 14)`	`9% ( 192)`	Chi-square=57.5 d.f.=16 P<0.001
Married		`70% ( 353)`	`73% ( 207)`	`77% ( 275)`	`78% ( 482)`	`83% ( 306)`	`76% (1623)`
Never married		`5% ( 26)`	`5% ( 14)`	`4% ( 15)`	`2% ( 10)`	`3% ( 10)`	`4% ( 75)`
Unknown		`0% ( 1)`	`0% ( 1)`	`1% ( 4)`	`0% ( 2)`	`0% ( 0)`	`0% ( 8)`
Widowed		`15% ( 74)`	`10% ( 28)`	`6% ( 23)`	`12% ( 74)`	`10% ( 37)`	`11% ( 236)`
Ethnicity : Unknown	2158	`0% ( 2)`	`1% ( 2)`	`1% ( 2)`	`0% ( 3)`	`1% ( 3)`	`1% ( 12)`	Chi-square=4.31 d.f.=8 P=0.828
Not Hisp/Latino		`96% ( 487)`	`95% ( 272)`	`95% ( 338)`	`97% ( 600)`	`96% ( 352)`	`96% (2049)`
Hisp/Latino		`3% ( 17)`	`4% ( 11)`	`5% ( 17)`	`3% ( 16)`	`3% ( 12)`	`3% ( 73)`
Race : Am Indian/Alaskan	2158	`0% ( 2)`	`0% ( 0)`	`0% ( 1)`	`0% ( 1)`	`0% ( 0)`	`0% ( 4)`	Chi-square=48.9 d.f.=24 P=0.002
Asian		`2% ( 9)`	`3% ( 9)`	`1% ( 4)`	`2% ( 12)`	`2% ( 8)`	`2% ( 42)`
Hawaiian/Other PI		`0% ( 0)`	`0% ( 0)`	`0% ( 1)`	`0% ( 1)`	`0% ( 0)`	`0% ( 2)`
Black		`6% ( 32)`	`5% ( 13)`	`2% ( 8)`	`4% ( 25)`	`4% ( 14)`	`4% ( 92)`
White		`91% ( 461)`	`88% ( 252)`	`93% ( 333)`	`93% ( 577)`	`93% ( 341)`	`92% (1964)`
More than one		`0% ( 2)`	`4% ( 10)`	`2% ( 7)`	`0% ( 3)`	`1% ( 4)`	`1% ( 26)`
Unknown		`0% ( 0)`	`0% ( 1)`	`1% ( 3)`	`0% ( 0)`	`0% ( 0)`	`0% ( 4)`
CDR-SB	2158	`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=2947 d.f.=4,2129 P<0.001
ADAS 13	2135	`6.67/ 9.33/12.67`	`8.25/11.00/14.33`	`9.00/13.00/17.00`	`14.67/18.67/23.33`	`24.33/29.67/35.00`	`10.00/15.00/22.00`	F=630 d.f.=4,2112 P<0.001
MMSE	2158	`29/29/30`	`29/29/30`	`28/29/29`	`26/27/29`	`21/23/25`	`26/28/29`	F=570 d.f.=4,2129 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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $270$&   $-11.00$&   $-2.00$&   $ 0.00$&   $-0.3850$&   $ 2.00$&   $11.00$&   $ 3.43$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $245$&   $-11.00$&   $-3.00$&   $-0.34$&   $-0.5740$&   $ 2.00$&   $11.00$&   $ 3.78$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $251$&   $-10.00$&   $-3.00$&   $-1.00$&   $-0.6570$&   $ 2.00$&   $10.00$&   $ 3.54$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 42$&   $ -8.00$&   $-2.00$&   $-1.00$&   $-0.2780$&   $ 2.00$&   $11.00$&   $ 3.77$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $161$&   $ -8.00$&   $-2.00$&   $ 1.67$&   $ 1.3700$&   $ 4.00$&   $15.00$&   $ 4.64$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 53$&   $ -1.67$&   $ 2.67$&   $ 4.33$&   $ 5.1600$&   $ 7.00$&   $18.00$&   $ 4.46$\tabularnewline
   ~~72&   $ 90$&   $ -2.67$&   $ 2.00$&   $ 4.67$&   $ 5.4300$&   $ 7.58$&   $23.70$&   $ 4.68$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 38$&   $  0.00$&   $ 3.33$&   $ 5.34$&   $ 7.1300$&   $ 7.83$&   $28.30$&   $ 6.57$\tabularnewline
   ~~96&   $  4$&   $ -2.67$&   $ 1.34$&   $ 4.00$&   $ 4.0000$&   $ 6.66$&   $10.70$&   $ 5.55$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $429$&   $-12.00$&   $-3.00$&   $ 0.00$&   $ 0.0583$&   $ 3.00$&   $16.00$&   $ 4.38$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $469$&   $-15.00$&   $-3.00$&   $-0.33$&   $ 0.0469$&   $ 3.00$&   $54.00$&   $ 5.08$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $371$&   $-11.00$&   $-3.00$&   $ 0.00$&   $ 1.0500$&   $ 4.00$&   $21.00$&   $ 5.56$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $315$&   $-14.00$&   $-2.00$&   $ 1.00$&   $ 2.0400$&   $ 5.00$&   $49.00$&   $ 7.47$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $252$&   $-12.00$&   $-2.00$&   $ 1.00$&   $ 3.4800$&   $ 6.00$&   $55.00$&   $ 9.57$\tabularnewline
   ~~60&   $139$&   $ -7.00$&   $ 0.00$&   $ 3.00$&   $ 5.5000$&   $ 8.16$&   $71.00$&   $10.90$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $ 99$&   $ -5.00$&   $ 1.84$&   $ 4.33$&   $ 5.6700$&   $ 8.00$&   $37.00$&   $ 6.80$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 72$&   $ -3.33$&   $ 2.67$&   $ 5.34$&   $ 6.8700$&   $ 9.42$&   $22.00$&   $ 6.19$\tabularnewline
   ~~96&   $ 27$&   $  1.00$&   $ 5.16$&   $ 7.67$&   $ 9.8300$&   $11.30$&   $38.70$&   $ 8.26$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  1$&   $  5.33$&   $ 5.33$&   $ 5.33$&   $ 5.3300$&   $ 5.33$&   $ 5.33$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $127$&   $-12.00$&   $-1.50$&   $ 2.00$&   $ 2.3800$&   $ 6.50$&   $23.00$&   $ 5.62$\tabularnewline
   ~~12&   $114$&   $-13.00$&   $ 1.00$&   $ 4.00$&   $ 4.8600$&   $ 8.83$&   $27.00$&   $ 6.44$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 32$&   $ -5.00$&   $ 3.00$&   $ 7.00$&   $ 9.2700$&   $13.80$&   $36.00$&   $ 9.45$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  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$&   $10.70$&   $ 3.07$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  1$&   $ 10.00$&   $10.00$&   $10.00$&   $10.0000$&   $10.00$&   $10.00$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $274$&   $ -4$&   $-1.0$&   $ 0.0$&   $-0.0547$&   $ 1.0$&   $ 4$&   $1.400$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $248$&   $ -8$&   $-1.0$&   $ 0.0$&   $-0.2540$&   $ 1.0$&   $ 4$&   $1.610$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $255$&   $ -4$&   $-1.0$&   $ 0.0$&   $-0.1880$&   $ 1.0$&   $ 4$&   $1.500$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 45$&   $ -5$&   $-1.0$&   $ 0.0$&   $-0.3780$&   $ 1.0$&   $ 4$&   $1.810$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $161$&   $ -7$&   $-1.0$&   $ 0.0$&   $-0.2730$&   $ 1.0$&   $ 4$&   $1.690$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 53$&   $-10$&   $-1.0$&   $ 0.0$&   $-0.1890$&   $ 0.0$&   $ 4$&   $1.970$\tabularnewline
   ~~72&   $ 90$&   $ -8$&   $-1.0$&   $ 0.0$&   $-0.3330$&   $ 1.0$&   $ 4$&   $2.020$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 37$&   $ -7$&   $-3.0$&   $ 0.0$&   $-1.1400$&   $ 0.0$&   $ 2$&   $1.960$\tabularnewline
   ~~96&   $  4$&   $  0$&   $ 0.0$&   $ 0.5$&   $ 0.5000$&   $ 1.0$&   $ 1$&   $0.577$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $430$&   $-10$&   $-2.0$&   $ 0.0$&   $-0.4490$&   $ 1.0$&   $ 5$&   $1.880$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $472$&   $-11$&   $-2.0$&   $ 0.0$&   $-0.4980$&   $ 1.0$&   $ 6$&   $2.060$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $376$&   $-11$&   $-2.0$&   $ 0.0$&   $-0.9120$&   $ 1.0$&   $ 6$&   $2.450$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $316$&   $-23$&   $-2.0$&   $-1.0$&   $-1.2400$&   $ 1.0$&   $ 6$&   $3.330$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $256$&   $-20$&   $-3.0$&   $-1.0$&   $-1.6000$&   $ 1.0$&   $ 5$&   $3.820$\tabularnewline
   ~~60&   $143$&   $-30$&   $-3.0$&   $-1.0$&   $-1.9900$&   $ 0.0$&   $ 4$&   $4.640$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $103$&   $-24$&   $-2.0$&   $ 0.0$&   $-1.5000$&   $ 1.0$&   $ 5$&   $4.240$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 78$&   $-20$&   $-3.0$&   $-1.0$&   $-1.6400$&   $ 1.0$&   $ 6$&   $4.360$\tabularnewline
   ~~96&   $ 27$&   $-12$&   $-2.0$&   $-1.0$&   $-1.4100$&   $ 0.5$&   $ 5$&   $3.720$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  1$&   $  2$&   $ 2.0$&   $ 2.0$&   $ 2.0000$&   $ 2.0$&   $ 2$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $131$&   $-16$&   $-3.0$&   $-1.0$&   $-1.1800$&   $ 1.0$&   $ 8$&   $3.070$\tabularnewline
   ~~12&   $118$&   $-19$&   $-4.0$&   $-2.0$&   $-2.3100$&   $ 0.0$&   $ 5$&   $4.050$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 33$&   $-12$&   $-6.0$&   $-3.0$&   $-4.0300$&   $-2.0$&   $ 2$&   $3.280$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  2$&   $ -4$&   $-3.0$&   $-2.0$&   $-2.0000$&   $-1.0$&   $ 0$&   $2.830$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  2$&   $ -5$&   $-4.5$&   $-4.0$&   $-4.0000$&   $-3.5$&   $-3$&   $1.410$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.0$&   $ 0.000$&   $ 0.0$&   $ 0.0879$&   $ 0.000$&   $ 2.5$&   $0.348$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $242$&   $-1.0$&   $ 0.000$&   $ 0.0$&   $ 0.1380$&   $ 0.000$&   $ 4.0$&   $0.514$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $254$&   $-1.0$&   $ 0.000$&   $ 0.0$&   $ 0.1770$&   $ 0.000$&   $ 5.0$&   $0.630$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 42$&   $-0.5$&   $ 0.000$&   $ 0.0$&   $ 0.4760$&   $ 0.500$&   $ 5.0$&   $1.130$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $156$&   $-0.5$&   $ 0.000$&   $ 0.0$&   $ 0.2020$&   $ 0.000$&   $ 5.0$&   $0.686$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 56$&   $-0.5$&   $ 0.000$&   $ 0.0$&   $ 0.5540$&   $ 0.500$&   $11.0$&   $1.710$\tabularnewline
   ~~72&   $ 94$&   $-0.5$&   $ 0.000$&   $ 0.0$&   $ 0.4260$&   $ 0.375$&   $10.0$&   $1.280$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 42$&   $-0.5$&   $ 0.000$&   $ 0.0$&   $ 0.6190$&   $ 0.500$&   $ 8.5$&   $1.540$\tabularnewline
   ~~96&   $  5$&   $ 0.0$&   $ 0.000$&   $ 0.0$&   $ 0.2000$&   $ 0.500$&   $ 0.5$&   $0.274$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $426$&   $-3.5$&   $-0.500$&   $ 0.0$&   $ 0.1310$&   $ 0.500$&   $ 3.0$&   $0.807$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $464$&   $-3.0$&   $-0.500$&   $ 0.0$&   $ 0.2040$&   $ 0.500$&   $ 5.5$&   $1.020$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $381$&   $-3.0$&   $-0.500$&   $ 0.0$&   $ 0.5630$&   $ 1.000$&   $11.5$&   $1.630$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $325$&   $-3.5$&   $-0.500$&   $ 0.0$&   $ 0.9080$&   $ 1.500$&   $12.5$&   $2.380$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $257$&   $-3.5$&   $-0.500$&   $ 0.0$&   $ 1.1200$&   $ 2.000$&   $16.0$&   $2.910$\tabularnewline
   ~~60&   $141$&   $-3.0$&   $-0.500$&   $ 0.0$&   $ 0.9260$&   $ 1.500$&   $14.5$&   $2.650$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $105$&   $-3.0$&   $-0.500$&   $ 0.0$&   $ 1.1700$&   $ 1.500$&   $15.5$&   $3.330$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 81$&   $-3.5$&   $-0.500$&   $ 0.0$&   $ 1.6500$&   $ 2.000$&   $15.0$&   $3.810$\tabularnewline
   ~~96&   $ 31$&   $-2.5$&   $-0.500$&   $ 0.0$&   $ 1.0800$&   $ 0.750$&   $11.5$&   $3.360$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  1$&   $-2.5$&   $-2.500$&   $-2.5$&   $-2.5000$&   $-2.500$&   $-2.5$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $131$&   $-2.5$&   $ 0.000$&   $ 0.5$&   $ 0.8130$&   $ 1.500$&   $ 9.0$&   $1.540$\tabularnewline
   ~~12&   $122$&   $-2.0$&   $ 0.125$&   $ 1.0$&   $ 1.8600$&   $ 2.500$&   $11.5$&   $2.520$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 33$&   $-1.0$&   $ 0.500$&   $ 2.5$&   $ 2.7000$&   $ 4.000$&   $ 8.5$&   $2.470$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  1$&   $ 3.0$&   $ 3.000$&   $ 3.0$&   $ 3.0000$&   $ 3.000$&   $ 3.0$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  4$&   $ 2.0$&   $ 4.250$&   $ 8.0$&   $ 7.3800$&   $11.100$&   $11.5$&   $4.640$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  3$&   $ 7.0$&   $ 7.750$&   $ 8.5$&   $10.0000$&   $11.500$&   $14.5$&   $3.970$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.500$&   $-0.2500$&   $ 0.000$&   $ 0.0303$&   $ 0.2500$&   $ 1.6200$&   $0.431$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $246$&   $-1.380$&   $-0.2500$&   $ 0.000$&   $ 0.0222$&   $ 0.2500$&   $ 1.6200$&   $0.437$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $256$&   $-1.380$&   $-0.2500$&   $ 0.000$&   $ 0.0511$&   $ 0.3750$&   $ 1.7500$&   $0.452$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 44$&   $-0.589$&   $-0.2500$&   $ 0.000$&   $-0.0361$&   $ 0.1250$&   $ 0.7500$&   $0.313$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $163$&   $-1.380$&   $-0.2500$&   $ 0.000$&   $ 0.0563$&   $ 0.3750$&   $ 2.1200$&   $0.495$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 57$&   $-1.430$&   $ 0.0000$&   $ 0.125$&   $ 0.1470$&   $ 0.3750$&   $ 1.3800$&   $0.495$\tabularnewline
   ~~72&   $ 91$&   $-1.000$&   $-0.1250$&   $ 0.125$&   $ 0.2060$&   $ 0.5000$&   $ 1.6200$&   $0.519$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 44$&   $-0.839$&   $-0.0312$&   $ 0.250$&   $ 0.2650$&   $ 0.6560$&   $ 1.8200$&   $0.586$\tabularnewline
   ~~96&   $  5$&   $-0.500$&   $-0.1250$&   $ 0.000$&   $ 0.0000$&   $ 0.1250$&   $ 0.5000$&   $0.364$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $428$&   $-2.120$&   $-0.3750$&   $-0.125$&   $-0.1040$&   $ 0.2500$&   $ 1.6200$&   $0.539$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $470$&   $-2.250$&   $-0.4240$&   $ 0.000$&   $-0.0709$&   $ 0.2500$&   $ 1.6200$&   $0.602$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $378$&   $-2.880$&   $-0.3750$&   $ 0.000$&   $-0.0280$&   $ 0.2770$&   $ 2.5000$&   $0.647$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $318$&   $-2.380$&   $-0.3750$&   $-0.125$&   $-0.0443$&   $ 0.3750$&   $ 2.5000$&   $0.637$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $250$&   $-2.500$&   $-0.5000$&   $-0.125$&   $-0.0975$&   $ 0.3120$&   $ 2.3600$&   $0.725$\tabularnewline
   ~~60&   $141$&   $-1.500$&   $-0.3750$&   $ 0.000$&   $ 0.0201$&   $ 0.5000$&   $ 1.7500$&   $0.596$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $102$&   $-2.120$&   $-0.3750$&   $ 0.000$&   $ 0.0115$&   $ 0.4690$&   $ 1.7500$&   $0.738$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 79$&   $-2.380$&   $-0.3750$&   $-0.125$&   $-0.0654$&   $ 0.2500$&   $ 2.0000$&   $0.682$\tabularnewline
   ~~96&   $ 29$&   $-2.500$&   $-0.5000$&   $-0.250$&   $-0.1160$&   $ 0.3750$&   $ 2.2100$&   $0.877$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  1$&   $-0.125$&   $-0.1250$&   $-0.125$&   $-0.1250$&   $-0.1250$&   $-0.1250$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $124$&   $-1.880$&   $-0.4060$&   $ 0.000$&   $-0.0592$&   $ 0.3750$&   $ 1.7500$&   $0.725$\tabularnewline
   ~~12&   $104$&   $-2.000$&   $-0.3750$&   $ 0.000$&   $-0.1370$&   $ 0.3750$&   $ 1.4300$&   $0.703$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 25$&   $-1.750$&   $-0.6250$&   $-0.286$&   $-0.2870$&   $ 0.0357$&   $ 1.0000$&   $0.617$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  2$&   $-0.875$&   $-0.6650$&   $-0.455$&   $-0.4550$&   $-0.2460$&   $-0.0357$&   $0.593$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  1$&   $-0.875$&   $-0.8750$&   $-0.875$&   $-0.8750$&   $-0.8750$&   $-0.8750$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $263$&   $-1.380$&   $-0.1250$&   $ 0.000$&   $0.01720$&   $0.125$&   $1.620$&   $0.361$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $241$&   $-1.500$&   $-0.1250$&   $ 0.000$&   $0.04300$&   $0.250$&   $2.120$&   $0.419$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $246$&   $-1.500$&   $-0.1250$&   $ 0.000$&   $0.04550$&   $0.250$&   $2.120$&   $0.449$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 41$&   $-1.380$&   $-0.1250$&   $ 0.000$&   $0.12100$&   $0.300$&   $2.120$&   $0.542$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $155$&   $-1.250$&   $-0.1550$&   $ 0.000$&   $0.11400$&   $0.250$&   $2.120$&   $0.490$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 54$&   $-0.750$&   $-0.1250$&   $ 0.000$&   $0.14100$&   $0.250$&   $2.460$&   $0.568$\tabularnewline
   ~~72&   $ 92$&   $-1.500$&   $-0.0104$&   $ 0.125$&   $0.27100$&   $0.500$&   $2.250$&   $0.635$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 43$&   $-2.380$&   $ 0.0000$&   $ 0.125$&   $0.32300$&   $0.625$&   $2.750$&   $0.813$\tabularnewline
   ~~96&   $  5$&   $-0.500$&   $-0.1250$&   $-0.125$&   $0.13200$&   $0.250$&   $1.160$&   $0.633$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $424$&   $-1.880$&   $-0.2500$&   $ 0.000$&   $0.00345$&   $0.375$&   $2.120$&   $0.561$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $463$&   $-2.750$&   $-0.2500$&   $ 0.000$&   $0.01660$&   $0.268$&   $2.250$&   $0.587$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $380$&   $-1.880$&   $-0.2500$&   $ 0.000$&   $0.10700$&   $0.500$&   $2.120$&   $0.644$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $317$&   $-2.250$&   $-0.2500$&   $ 0.125$&   $0.15000$&   $0.500$&   $2.140$&   $0.706$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $245$&   $-1.750$&   $-0.2500$&   $ 0.125$&   $0.22500$&   $0.500$&   $2.880$&   $0.710$\tabularnewline
   ~~60&   $137$&   $-1.620$&   $-0.1790$&   $ 0.125$&   $0.27000$&   $0.625$&   $2.500$&   $0.783$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $106$&   $-1.620$&   $-0.2500$&   $ 0.125$&   $0.19300$&   $0.554$&   $2.290$&   $0.675$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 83$&   $-1.250$&   $-0.2500$&   $ 0.125$&   $0.29400$&   $0.875$&   $2.500$&   $0.851$\tabularnewline
   ~~96&   $ 30$&   $-1.120$&   $-0.1120$&   $ 0.357$&   $0.25300$&   $0.500$&   $2.120$&   $0.650$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  1$&   $ 0.125$&   $ 0.1250$&   $ 0.125$&   $0.12500$&   $0.125$&   $0.125$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $130$&   $-2.750$&   $-0.2500$&   $ 0.000$&   $0.04210$&   $0.479$&   $1.620$&   $0.616$\tabularnewline
   ~~12&   $120$&   $-1.620$&   $ 0.0000$&   $ 0.125$&   $0.21800$&   $0.500$&   $2.120$&   $0.518$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 33$&   $-1.540$&   $-0.1250$&   $ 0.000$&   $0.12800$&   $0.375$&   $1.500$&   $0.591$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  1$&   $ 0.000$&   $ 0.0000$&   $ 0.000$&   $0.00000$&   $0.000$&   $0.000$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  4$&   $ 0.000$&   $ 0.0938$&   $ 0.625$&   $0.84400$&   $1.380$&   $2.120$&   $0.992$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  2$&   $ 0.000$&   $ 0.4550$&   $ 0.911$&   $0.91100$&   $1.370$&   $1.820$&   $1.290$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $273$&   $-1.140$&   $-0.10300$&   $ 0.0000$&   $ 0.01780$&   $ 0.1280$&   $ 0.8210$&   $0.253$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $246$&   $-0.751$&   $-0.10300$&   $ 0.0000$&   $ 0.02290$&   $ 0.1280$&   $ 1.4600$&   $0.253$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $256$&   $-0.985$&   $-0.10300$&   $ 0.0000$&   $ 0.03900$&   $ 0.1790$&   $ 1.1800$&   $0.301$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 44$&   $-0.526$&   $-0.10300$&   $-0.0256$&   $ 0.00677$&   $ 0.1030$&   $ 0.7440$&   $0.225$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $164$&   $-0.985$&   $-0.10700$&   $ 0.0418$&   $ 0.04310$&   $ 0.1670$&   $ 1.7200$&   $0.304$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 57$&   $-0.725$&   $-0.04660$&   $ 0.1330$&   $ 0.11100$&   $ 0.2210$&   $ 0.7270$&   $0.314$\tabularnewline
   ~~72&   $ 91$&   $-1.010$&   $ 0.00304$&   $ 0.1360$&   $ 0.15300$&   $ 0.2730$&   $ 1.3000$&   $0.322$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 44$&   $-0.536$&   $-0.02790$&   $ 0.0675$&   $ 0.16300$&   $ 0.3020$&   $ 1.1600$&   $0.347$\tabularnewline
   ~~96&   $  5$&   $-0.153$&   $ 0.02900$&   $ 0.0547$&   $ 0.02770$&   $ 0.0789$&   $ 0.1290$&   $0.107$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $430$&   $-2.080$&   $-0.21900$&   $-0.0263$&   $-0.03500$&   $ 0.1500$&   $ 1.5900$&   $0.376$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $472$&   $-1.690$&   $-0.23500$&   $ 0.0000$&   $-0.01750$&   $ 0.1840$&   $ 1.6700$&   $0.399$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $379$&   $-1.690$&   $-0.20500$&   $ 0.0000$&   $ 0.02530$&   $ 0.2310$&   $ 1.7400$&   $0.438$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $314$&   $-1.730$&   $-0.20500$&   $ 0.0222$&   $ 0.04000$&   $ 0.2920$&   $ 1.9900$&   $0.453$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $249$&   $-2.310$&   $-0.24700$&   $ 0.0256$&   $ 0.03160$&   $ 0.3080$&   $ 2.7100$&   $0.529$\tabularnewline
   ~~60&   $139$&   $-1.210$&   $-0.14100$&   $ 0.0513$&   $ 0.07250$&   $ 0.3260$&   $ 1.1300$&   $0.438$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $102$&   $-1.130$&   $-0.16700$&   $ 0.0466$&   $ 0.09410$&   $ 0.3860$&   $ 1.4800$&   $0.469$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 79$&   $-1.070$&   $-0.22100$&   $ 0.0027$&   $ 0.03700$&   $ 0.2200$&   $ 1.6000$&   $0.495$\tabularnewline
   ~~96&   $ 29$&   $-1.090$&   $-0.29100$&   $ 0.0351$&   $ 0.08920$&   $ 0.2890$&   $ 2.5900$&   $0.653$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  1$&   $ 0.113$&   $ 0.11300$&   $ 0.1130$&   $ 0.11300$&   $ 0.1130$&   $ 0.1130$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $120$&   $-1.690$&   $-0.29800$&   $ 0.0232$&   $-0.01190$&   $ 0.2840$&   $ 1.5100$&   $0.554$\tabularnewline
   ~~12&   $101$&   $-1.310$&   $-0.23100$&   $-0.0115$&   $-0.01200$&   $ 0.2490$&   $ 1.1300$&   $0.485$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 25$&   $-1.430$&   $-0.31800$&   $-0.0256$&   $-0.02570$&   $ 0.4060$&   $ 0.8820$&   $0.496$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  2$&   $-0.543$&   $-0.39400$&   $-0.2450$&   $-0.24500$&   $-0.0957$&   $ 0.0535$&   $0.422$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  1$&   $-0.191$&   $-0.19100$&   $-0.1910$&   $-0.19100$&   $-0.1910$&   $-0.1910$&   $$\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$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $265$&   $-0.879$&   $-0.0513$&   $ 0.0000$&   $ 0.00909$&   $0.0769$&   $0.8460$&   $0.193$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $241$&   $-1.210$&   $-0.0481$&   $ 0.0000$&   $ 0.04030$&   $0.0980$&   $1.6200$&   $0.266$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $246$&   $-1.130$&   $-0.0685$&   $ 0.0000$&   $ 0.04590$&   $0.1030$&   $2.0000$&   $0.305$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $ 41$&   $-1.330$&   $ 0.0000$&   $ 0.0513$&   $ 0.11900$&   $0.2290$&   $2.0500$&   $0.469$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $156$&   $-1.050$&   $-0.0516$&   $ 0.0000$&   $ 0.08570$&   $0.1290$&   $1.6800$&   $0.341$\tabularnewline
   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~60&   $ 54$&   $-0.540$&   $-0.0447$&   $ 0.0395$&   $ 0.16500$&   $0.2110$&   $2.5400$&   $0.509$\tabularnewline
   ~~72&   $ 92$&   $-0.994$&   $-0.0211$&   $ 0.0423$&   $ 0.17600$&   $0.2810$&   $2.5200$&   $0.481$\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 43$&   $-1.540$&   $ 0.0000$&   $ 0.0830$&   $ 0.25500$&   $0.2770$&   $2.9500$&   $0.680$\tabularnewline
   ~~96&   $  5$&   $-0.564$&   $-0.4290$&   $-0.0236$&   $-0.17000$&   $0.0789$&   $0.0905$&   $0.306$\tabularnewline
\hline
{\bfseries MCI}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~6&   $426$&   $-1.460$&   $-0.1670$&   $ 0.0206$&   $ 0.05150$&   $0.2540$&   $1.9900$&   $0.411$\tabularnewline
\rowcolor[gray]{.9}   ~~12&   $463$&   $-2.040$&   $-0.1280$&   $ 0.0425$&   $ 0.08540$&   $0.2870$&   $2.0900$&   $0.463$\tabularnewline
   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~24&   $380$&   $-1.410$&   $-0.1030$&   $ 0.1030$&   $ 0.18700$&   $0.3900$&   $2.4100$&   $0.532$\tabularnewline
   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~36&   $316$&   $-2.140$&   $-0.1030$&   $ 0.1440$&   $ 0.25400$&   $0.4890$&   $2.5100$&   $0.619$\tabularnewline
   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~48&   $245$&   $-2.110$&   $-0.1030$&   $ 0.1540$&   $ 0.28400$&   $0.5710$&   $2.6200$&   $0.648$\tabularnewline
   ~~60&   $137$&   $-1.050$&   $-0.1030$&   $ 0.1660$&   $ 0.32500$&   $0.6910$&   $2.4000$&   $0.676$\tabularnewline
\rowcolor[gray]{.9}   ~~66&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~72&   $106$&   $-1.100$&   $-0.1000$&   $ 0.1450$&   $ 0.26300$&   $0.4990$&   $2.2500$&   $0.614$\tabularnewline
\hline
{\bfseries Dementia}&&&&&&&&\tabularnewline
\rowcolor[gray]{.9}   ~~84&   $ 83$&   $-1.340$&   $-0.1060$&   $ 0.2000$&   $ 0.42000$&   $0.8910$&   $2.4000$&   $0.817$\tabularnewline
   ~~96&   $ 30$&   $-0.491$&   $-0.0391$&   $ 0.1140$&   $ 0.32000$&   $0.5540$&   $2.0300$&   $0.615$\tabularnewline
\rowcolor[gray]{.9}   ~~108&   $  1$&   $ 0.134$&   $ 0.1340$&   $ 0.1340$&   $ 0.13400$&   $0.1340$&   $0.1340$&   $$\tabularnewline
   ~~3&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~6&   $130$&   $-2.500$&   $-0.1470$&   $ 0.1260$&   $ 0.10500$&   $0.4100$&   $1.3300$&   $0.524$\tabularnewline
   ~~12&   $121$&   $-1.460$&   $ 0.0769$&   $ 0.3160$&   $ 0.33400$&   $0.5830$&   $1.5700$&   $0.469$\tabularnewline
\rowcolor[gray]{.9}   ~~18&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~24&   $ 33$&   $-0.374$&   $ 0.0097$&   $ 0.3600$&   $ 0.42700$&   $0.7780$&   $1.8900$&   $0.522$\tabularnewline
\rowcolor[gray]{.9}   ~~30&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~36&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~42&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~48&   $  1$&   $ 0.718$&   $ 0.7180$&   $ 0.7180$&   $ 0.71800$&   $0.7180$&   $0.7180$&   $$\tabularnewline
\rowcolor[gray]{.9}   ~~54&   $  0$&   $$&   $$&   $$&   $$&   $$&   $$&   $$\tabularnewline
   ~~60&   $  4$&   $-0.241$&   $ 0.4780$&   $ 0.7580$&   $ 0.97900$&   $1.2600$&   $2.6400$&   $1.200$\tabularnewline
\rowcolor[gray]{.9}   ~~72&   $  2$&   $ 0.675$&   $ 0.8240$&   $ 0.9730$&   $ 0.97300$&   $1.1200$&   $1.2700$&   $0.421$\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