rewie_rsq: Computes R-squared for RE panel models
In rewie: Data Preparation and Diagnostics for Random Effects Within Estimator

Description Usage Arguments Details Value Author(s) Examples

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

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

`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

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.

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.

Scott Duxbury, Assistant Professor of Sociology at University of North Carolina, Chapel Hill

  
  
    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)