::Free Statistics and Forecasting Software::

v1.2.1

:: Differences in COLLES subscales - Free Statistics Software (Calculator) ::

All rights reserved. The non-commercial (academic) use of this software is free of charge. The only thing that is asked in return is to cite this software when results are used in publications.

This free online software (calculator) computes the analysis of the Differences in COLLES subscales as published in:

Wessa P, Holliday IE (2012) Does Reviewing Lead to Better Learning and Decision Making? Answers from a Randomized Stock Market Experiment. PLoS ONE 7(5): e37719. doi:10.1371/journal.pone.0037719

 Send output to: Browser Blue - Charts White Browser Black/White CSV MS Excel MS Word Chart options Width: Height: Compute

 Source code of R module y <- read.csv(file="http://www.wessa.net/download/PRexperiment/colles.csv",header=T) for (i in 1:48) y <- y[!is.na(y[,paste("C",i,sep="")]),] x <- y[y\$Year==0,] #we need to do this year by year (the order of the preferred and actual items changed!) p_rel_0 <- x\$C1 + x\$C3 + x\$C5 + x\$C7 a_rel_0 <- x\$C2 + x\$C4 + x\$C6 + x\$C8 p_refl_0 <- x\$C9 + x\$C11 + x\$C13 + x\$C15 a_refl_0 <- x\$C10 + x\$C12 + x\$C14 + x\$C16 p_int_0 <- x\$C17 + x\$C19 + x\$C21 + x\$C23 a_int_0 <- x\$C18 + x\$C20 + x\$C22 + x\$C24 p_cog_0 <- x\$C25 + x\$C27 + x\$C29 + x\$C31 a_cog_0 <- x\$C26 + x\$C28 + x\$C30 + x\$C32 p_aff_0 <- x\$C33 + x\$C35 + x\$C37 + x\$C39 a_aff_0 <- x\$C34 + x\$C36 + x\$C38 + x\$C40 p_mean_0 <- x\$C41 + x\$C43 + x\$C45 + x\$C47 a_mean_0 <- x\$C42 + x\$C44 + x\$C46 + x\$C48 x <- y[y\$Year==1,] p_rel_1 <- x\$C1 + x\$C3 + x\$C5 + x\$C7 a_rel_1 <- x\$C2 + x\$C4 + x\$C6 + x\$C8 p_refl_1 <- x\$C9 + x\$C11 + x\$C13 + x\$C15 a_refl_1 <- x\$C10 + x\$C12 + x\$C14 + x\$C16 p_int_1 <- x\$C17 + x\$C19 + x\$C21 + x\$C23 a_int_1 <- x\$C18 + x\$C20 + x\$C22 + x\$C24 p_cog_1 <- x\$C25 + x\$C27 + x\$C29 + x\$C31 a_cog_1 <- x\$C26 + x\$C28 + x\$C30 + x\$C32 p_aff_1 <- x\$C33 + x\$C35 + x\$C37 + x\$C39 a_aff_1 <- x\$C34 + x\$C36 + x\$C38 + x\$C40 p_mean_1 <- x\$C41 + x\$C43 + x\$C45 + x\$C47 a_mean_1 <- x\$C42 + x\$C44 + x\$C46 + x\$C48 x <- y[y\$Year==2,] p_rel_2 <- x\$C1 + x\$C3 + x\$C5 + x\$C7 a_rel_2 <- x\$C2 + x\$C4 + x\$C6 + x\$C8 p_refl_2 <- x\$C9 + x\$C11 + x\$C13 + x\$C15 a_refl_2 <- x\$C10 + x\$C12 + x\$C14 + x\$C16 p_int_2 <- x\$C17 + x\$C19 + x\$C21 + x\$C23 a_int_2 <- x\$C18 + x\$C20 + x\$C22 + x\$C24 p_cog_2 <- x\$C25 + x\$C27 + x\$C29 + x\$C31 a_cog_2 <- x\$C26 + x\$C28 + x\$C30 + x\$C32 p_aff_2 <- x\$C33 + x\$C35 + x\$C37 + x\$C39 a_aff_2 <- x\$C34 + x\$C36 + x\$C38 + x\$C40 p_mean_2 <- x\$C41 + x\$C43 + x\$C45 + x\$C47 a_mean_2 <- x\$C42 + x\$C44 + x\$C46 + x\$C48 x <- y[y\$Year==3,] p_rel_3 <- x\$C1 + x\$C3 + x\$C5 + x\$C7 a_rel_3 <- x\$C2 + x\$C4 + x\$C6 + x\$C8 p_refl_3 <- x\$C9 + x\$C11 + x\$C13 + x\$C15 a_refl_3 <- x\$C10 + x\$C12 + x\$C14 + x\$C16 p_int_3 <- x\$C17 + x\$C19 + x\$C21 + x\$C23 a_int_3 <- x\$C18 + x\$C20 + x\$C22 + x\$C24 p_cog_3 <- x\$C25 + x\$C27 + x\$C29 + x\$C31 a_cog_3 <- x\$C26 + x\$C28 + x\$C30 + x\$C32 p_aff_3 <- x\$C33 + x\$C35 + x\$C37 + x\$C39 a_aff_3 <- x\$C34 + x\$C36 + x\$C38 + x\$C40 p_mean_3 <- x\$C41 + x\$C43 + x\$C45 + x\$C47 a_mean_3 <- x\$C42 + x\$C44 + x\$C46 + x\$C48 bitmap(file="pic.png") b <- boxplot(cbind((c(p_rel_0, p_rel_1, a_rel_2, a_rel_3) - c(a_rel_0, a_rel_1, p_rel_2, p_rel_3)), (c(p_refl_0, p_refl_1, a_refl_2, a_refl_3) - c(a_refl_0, a_refl_1, p_refl_2, p_refl_3)), (c(p_int_0, p_int_1, a_int_2, a_int_3) - c(a_int_0, a_int_1, p_int_2, p_int_3)), (c(p_cog_0, p_cog_1, a_cog_2, a_cog_3) - c(a_cog_0, a_cog_1, p_cog_2, p_cog_3)), (c(p_aff_0, p_aff_1, a_aff_2, a_aff_3) - c(a_aff_0, a_aff_1, p_aff_2, p_aff_3)), (c(p_mean_0, p_mean_1, a_mean_2, a_mean_3) - c(a_mean_0, a_mean_1, p_mean_2, p_mean_3))), notch=T, axes=F, main="COLLES Subscale Differences") axis(2) names=c("relevance", "refl. thinking", "interactivity", "cog. demand", "aff. support", "meaning") cex.axis=0.5 text(axTicks(1), par("usr")[3], srt=45, adj=1, labels=names, xpd=T, cex=0.8) dev.off() load(file="createtable") a<-table.start() a<-table.row.start(a) a<-table.element(a,"Utility Hypothesis - COLLES Subscale Differences",1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste("
",RC.texteval("summary(b\$stats);b\$conf"),"
",sep="")) a<-table.row.end(a) a<-table.end(a) table.save(a,file="mytable.tab")
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 Cite this software as: P. Wessa and I. E. Holliday, 2012, Differences in COLLES subscales (v1.0.1) in Free Statistics Software (v1.2.1), Office for Research Development and Education, URL http://www.wessa.net/rwasp_PRcolles.wasp/ The R code is based on : Wessa P, Holliday IE (2012) Does Reviewing Lead to Better Learning and Decision Making? Answers from a Randomized Stock Market Experiment. PLoS ONE 7(5): e37719. doi:10.1371/journal.pone.0037719
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