eRm (version 1.0-1)

llra.datprep: Prepare Data Set for LLRA Analysis

Description

Converts wide data matrix in long format, sorts subjects according to groups and builds assigment vector.

Usage

llra.datprep(X, mpoints, groups, baseline)

Arguments

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.

Value

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.

Details

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.

See Also

The function that uses this is LLRA. The values from llra.datprep can be passed to build_W.

Examples

# NOT RUN {
    # 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) 
# }