Prepare Data Set for LLRA Analysis
Converts wide data matrix in long format, sorts subjects according to groups and builds assigment vector.
llra.datprep(X, mpoints, groups, baseline)
X |
Data matrix as described in Hatzinger and Rusch (2009). It must be of wide format, e.g. for each person all item answers are written in columns for t1, t2, t3 etc. Hence each row corresponds to all observations for a single person. Missing values are not allowed. |
mpoints |
The number of time points. |
groups |
Vector, matrix or data frame with subject/treatment covariates. |
baseline |
An optional vector with the baseline values for the columns in group. |
The function converts a data matrix from wide to long fromat as needed for LLRA. Additionally it sorts the subjects according to the different treatment/covariate groups. The group with the lowest (alpha-)numerical value will be the baseline.
Treatment and covariate groups are either defined by a vector, or by a matrix or data frame. The latter will be combined to a vector of groups corresponding to a combination of each factor level per column with the factor levels of the other column. The (constructed or passed) vector will then be used to create the assignment vector.
Returns a list with the components
X |
Data matrix in long format with subjects sorted by groups. |
assign.vec |
The assignment vector. |
grp_n |
A vector of the number of subjects in each group. |
Reinhold Hatzinger
# example 3 items, 3 timepoints, n=10, 2x2 treatments
dat<-sim.rasch(10,9)
tr1<-sample(c("a","b"),10,r=TRUE)
tr2<-sample(c("x","y"),10,r=TRUE)
# one treatment
res<-llra.datprep(dat,mpoints=3,groups=tr1)
res<-llra.datprep(dat,mpoints=3,groups=tr1,baseline="b")
# two treatments
res<-llra.datprep(dat,mpoints=3,groups=cbind(tr1,tr2))
res<-llra.datprep(dat,mpoints=3,groups=cbind(tr1,tr2),baseline=c("b","x"))
# two treatments - data frame
tr.dfr<-data.frame(tr1, tr2)
res<-llra.datprep(dat,mpoints=3,groups=tr.dfr)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.