rewie (version 0.1.0)

rewie.rsq: Computes R-squared for RE panel models

Description

Calculates R-squared for BW, REWE, REWIE, and BW. Includes idiosyncratic R-squared, between R-squared, homogneous-within R-squared, and within R-Squared.

Usage

rewie.rsq(model,timevar,csvar,df)

Arguments

model

is an lmerMod object fitted by calling the lmer() function in lme4.

timevar

is a character string providing the name of the time indicator variable.

csvar

is a character string providing the name of the cross-section indicator variable.

df

is a dataframe containing y, timevar, and csvar

Value

Returns the results for R-squares

Rsq.total

is the overall R-squared.

Rsq.within

is the within R-squared.

Rsq.time

is the time (homogenous-within) R-squared.

Rsq.idio

is the idiosyncratic R-squared.

Rsq.betw

is the between R-squared.

%% ~Describe the value returned %% If it is a LIST, use %% \item{comp1 }{Description of 'comp1'} %% \item{comp2 }{Description of 'comp2'} %% ...

Details

Calculates the R-squared for each level of variation. It is calculated by computing the proportion of remaining variance to overall variance the model and then subtracting the quotient from 1.

Examples

# NOT RUN {
  
# }
# NOT RUN {
  
# }
# NOT RUN {
    require(plm)
    require(lme4)

    data("Crime")
    output<-lmer(lcrmrte~ldensity+(1|county)+(1|year),data=Crime)
    rewie.rsq(output,csvar="county",timevar="year",df=Crime)


  
# }