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Data X:
Group Phage % Kill % Lyt 1 IL6 IL2 TNF A1(+ve) 76.1 72.2 1.16 536.54 195.41 182.08 72.8 74.1 1.07 421.12 182.98 170.91 80.5 66.5 1.32 530.59 201.55 193.43 A2 76.23 74.2 1.28 465.11 193.61 169.41 73.18 71.3 1.12 466.01 187.8 157.98 80.11 76.8 1.23 465.27 178.26 178.76 A3 79.3 75.8 1.42 379.68 188.15 165.73 76.4 70.2 1.22 358.96 175.81 156.12 85.1 80.5 1.57 385.21 198.27 171.55 A4 80.27 77.2 1.44 405.77 180.09 167.09 76.39 71.5 1.37 420.21 170.21 168.87 85.87 80.1 1.57 390.65 189.54 173.11 A5 (-) 89 85.4 1.72 239.43 161.61 136.94 85.2 79.5 0.98 226.99 169.87 149.8 93.8 89.9 2.2 250.22 170.92 129.44
Names of X columns:
sid group Phage % Kill % Lyt 1 IL6 IL2 TNFcue flanker mean_rt
Response : Variable 1
Within Ss Factor : Variable 2
Within Ss Factor : Variable 3
Between Ss Factor : Variable 4
Subject Identifier Column : Variable 5
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R Code
par5 <- '1' par4 <- '2' par3 <- '4' par2 <- '3' par1 <- '5' cat1 <- as.numeric(par1) # cat2<- as.numeric(par2) # cat3 <- as.numeric(par3) cat4 <-as.numeric(par4) cat5 <-as.numeric(par5) x <- t(x) x1<-as.numeric(x[,cat1]) wf1<-as.character(x[,cat2]) wf2 <- as.character(x[,cat3]) bf1 <- as.character(x[,cat4]) sid<- as.character(x[,cat5]) # author of ez changed within subjects variable name from sid to wid xdf<-data.frame(x1,wf1, wf2, bf1, sid) (V1<-dimnames(y)[[1]][cat1]) (V2<-dimnames(y)[[1]][cat2]) (V3 <-dimnames(y)[[1]][cat3]) (V4 <-dimnames(y)[[1]][cat4]) (V5 <-dimnames(y)[[1]][cat5]) names(xdf)<-c(V1, V2, V3, V4, V5) library(ez) library(Cairo) (ezout <- ezANOVA(data=xdf, dv=.(mean_rt), wid=.(sid), within=.(cue, flanker), between=.(group) ) ) load(file='createtable') a<-table.start() nr <- nrow(ezout$ANOVA) nc <- ncol(ezout$ANOVA) a<-table.row.start(a) a<-table.element(a,'Repeated Measures ANOVA', nc+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'effect', 1,TRUE) a<-table.element(a,'Dfn',1,TRUE) a<-table.element(a,'DFd', 1,TRUE) a<-table.element(a, 'F', 1,TRUE) a<-table.element(a,'p', 1,TRUE) a<-table.element(a,'p<0.05', 1,TRUE) a<-table.element(a, 'ges', 1,TRUE) # generalized eta-sq - was partial eta-sq in earlier version a<-table.row.end(a) for ( i in 1:nr){ a<-table.row.start(a) a<-table.element(a,ezout$ANOVA$Effect[i], 1, TRUE) for(j in 2:nc){ if ( j != 6) # author of ez reduced number of columns in output from 8 a<-table.element(a,round(ezout$ANOVA[[j]][i], digits=3), 1, FALSE) else a<-table.element(a, ezout$ANOVA[[j]][i], 1, FALSE) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() nr <- nrow(ezout$Mauchly) nc <- ncol(ezout$Mauchly) a<-table.row.start(a) a<-table.element(a,'Mauchlys Test for Sphericity', nc+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'effect', 1,TRUE) a<-table.element(a,'W',1,TRUE) a<-table.element(a,'p', 1,TRUE) a<-table.element(a,'p<0.05', 1,TRUE) a<-table.row.end(a) for ( i in 1:nr){ a<-table.row.start(a) a<-table.element(a,ezout$Mauchly$Effect[i], 1, TRUE) for(j in 2:nc){ if (j != 4) a<-table.element(a,round(ezout$Mauchly[[j]][i], digits = 3), 1, FALSE) else a<-table.element(a,ezout$Mauchly[[j]][i], 1, FALSE) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() nr <- nrow(ezout$Spher) nc <- ncol(ezout$Sphe) a<-table.row.start(a) a<-table.element(a,'Sphericity Corrections', nc+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'effect', 1,TRUE) a<-table.element(a,'GGe',1,TRUE) a<-table.element(a,'p[GG]', 1,TRUE) a<-table.element(a,'p[GG]<0.05', 1,TRUE) a<-table.element(a,'HFe', 1,TRUE) a<-table.element(a,'p[HF]', 1,TRUE) a<-table.element(a,'p[HF]<0.05', 1,TRUE) a<-table.row.end(a) for ( i in 1:nr){ a<-table.row.start(a) a<-table.element(a,ezout$Spher$Effect[i], 1, TRUE) for(j in 2:nc){ if ( ! ((j == 4) | (j == 7)) ) a<-table.element(a,round(ezout$Spher[[j]][i], digits=3), 1, FALSE) else a<-table.element(a,ezout$Spher[[j]][i], 1, FALSE) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.tab') ezP.between<-ezPlot(data = xdf, dv = .(mean_rt), between = .(group), wid = .(sid), do_lines=FALSE, x_lab='group', y_lab='RT' , x=.(group)) bitmap(file = 'between.cairo') print(ezP.between) dev.off() ezstats_between<-ezStats(data = xdf, dv = .(mean_rt), between =.(group), wid = .(sid)) a<-table.start() nr <- nrow(ezstats_between) nc <- ncol(ezstats_between) a<-table.row.start(a) a<-table.element(a,'Between Effects Comparisons', nc+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) for(i in 1:nc){ a<-table.element(a, names(ezstats_between)[i], 1,TRUE) } a<-table.row.end(a) for ( i in 1:nr){ a<-table.row.start(a) a<-table.element(a,ezstats_between[[1]][i], 1, TRUE) for(j in 2:nc){ a<-table.element(a,ezstats_between[[j]][i], 1, FALSE) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable3.tab') ezP.within<-ezPlot(data = xdf, dv = .(mean_rt), within = .(cue, flanker), wid = .(sid), do_lines=TRUE, x_lab='flanker', y_lab='RT' , x=.(flanker), split=.(cue), split_lab = 'cue') bitmap(file = 'within.cairo') print(ezP.within) dev.off() ezstats_within <- ezStats(data = xdf, dv = .(mean_rt), within = .(cue, flanker), wid = .(sid)) a<-table.start() nr <- nrow(ezstats_within) nc <- ncol(ezstats_within) a<-table.row.start(a) a<-table.element(a,'Within Effects Comparisons', nc+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) for(i in 1:nc){ a<-table.element(a, names(ezstats_within)[i], 1,TRUE) } a<-table.row.end(a) for ( i in 1:nr){ a<-table.row.start(a) a<-table.element(a,ezstats_within[[1]][i], 1, TRUE) for(j in 2:nc){ a<-table.element(a, ezstats_within[[j]][i], 1, FALSE) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable4.tab')
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