make.univ | R Documentation |
Longitudinal data is often stored in multivariate or wide form. In multivariate form, each row contains data from one subject, and repeated measures variables are indexed by different names (e.g., OUTCOME.T1, OUTCOME.T2, OUTCOME.T3). In repeated measures designs and growth modeling, data needs to be converted to univariate or stacked form where each row represents one of the repeated measures indexed by a TIME variable nested within subject. In univariate form, each subject has as many rows of data as there are time points. R has several functions to convert data from wide to long formats and vice versa including reshape. The code used in make.univ borrows heavily from code provided in Chambers and Hastie (1991).
make.univ(x,dvs,tname="TIME", outname="MULTDV")
x |
A dataframe in multivariate form. |
dvs |
A subset dataframe of x containing the repeated measures columns. Note that the repeated measures must be ordered from Time 1 to Time N for this function to work properly. |
tname |
An optional name for the new time variable. Defaults to TIME. |
outname |
An optional name for the outcome variable name. Defaults to MULTDV. |
Returns a dataframe in univariate (i.e., stacked) form with a TIME variable representing the repeated observations, and a variable named MULTDV representing the time-indexed variable. The TIME variable begins with 0.
Paul Bliese pdbliese@gmail.com
Bliese, P. D., & Ployhart, R. E. (2002). Growth modeling using random coefficient models: Model building, testing and illustrations. Organizational Research Methods, 5, 362-387.
Chambers, J. M., & Hastie, T. J. (1991). Statistical models in S. CRC Press, Inc..
mult.make.univ
reshape
data(univbct) #a dataframe in univariate form for job satisfaction TEMP<-univbct[3*1:495,c(22,1:17)] #convert back to multivariate form #Transform data to univariate form TEMP2<-make.univ(x=TEMP,dvs=TEMP[,c(10,13,16)]) #Same as above, but renaming repeated variable TEMP3<-make.univ(x=TEMP,dvs=TEMP[,c(10,13,16)],outname="JOBSAT")
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