ContigencyTables {DIFplus} | R Documentation |
This function creates contigency tables by strata for each item. Both dichotomous and polytomous item responses are allowed. It also handles missing responses and returns a cleaned data set with no missing data.
ContigencyTables (Response.data, Response.code=c(0,1),
Group, group.names=NULL, Stratum=NULL, Cluster=NULL,
missing.code="NA", missing.impute="LW", print.information=TRUE)
Response.data |
A scored item responses matrix in the form of matrix or data frame. This matrix should not include any other variables (group, stratum, cluser, etc.). |
Response.code |
A numerical vector of all possible item responses. By default, Response.code=c(0,1). |
Group |
The variable of group membership (e.g., gender). Its length should be equal to the sample size of the item response matrix. |
group.names |
Names for each defined group (e.g., c('Male','Female')). This argument is optional. By default, group.names=NULL. If not provided, group names of "Group.1, Group.2, etc." will be automatically generated. |
Stratum |
The matching variable. By default, Stratum=NULL. If not provided, the observed total score will be used. |
Cluster |
The cluster variable. Its length should be equal to the sample size of the item response matrix. By default, Cluster=NULL. This variable will not be used to generate contigency tables. It will be included in the returned data set for DIF analysis. |
missing.code |
Indication of how missing values were defined in the data. By default, missing.code="NA". |
missing.impute |
The approach selected to handle missing item responses. By default, missing.impute="LW", indicating the list-wise
deletion will be used. Other options include: "PM" (person mean or row mean imputation),"IM" (item mean or column mean imputation),
"TW" (two-way imputation), "LR" (logistic regression imputation), and EM (EM imputation). Check the package "TestDataImputation"
(https://cran.r-project.org/package=TestDataImputation) for more details. |
print.information |
Indicator of whether function running information is printed on screen. By default, print.information=TRUE. |
This function creats contigency tables.
A list of strata statistcs, contigency tables, etc.
Strata.stats |
Summary statistics for each item: n.valid.strata, n.valid.category, and also sample sizes for each stratum across items. |
c.table.list.all |
A list that contains all contigency tables across items and strata. |
c.table.list.valid |
A list that contains only valid contigency tables across items and strata. Strata that have missing item response categories or zero marginal means are removed. |
data.out |
A cleaned data set with variables "Group", "Group.factor","Cluster", "Stratum", and all item responses (with missing data handled). |
#Specify the item responses matrix
data(data.adult)
Response.data<-data.adult[,2:13]
#Run the function with specifications
c.table.out<-ContigencyTables(Response.data, Response.code=c(0,1),
Group=data.adult$Group, group.names=NULL,
Stratum=NULL, Cluster=NULL, missing.code="NA",
missing.impute= "LW",print.information = TRUE)
#Obtain results
c.tables.all<-c.table.out$c.table.list.all
c.tables.valid<-c.table.out$c.table.list.valid
c.table.out$Strata.stats
data.use<-c.table.out$data.out