[R] How to calculate the "McFadden R-square" for LOGIT model?

[Christofer Bogaso]

Please ignore this mail. I got a solution by using 'pscl' package!

On Thu, Apr 12, 2012 at 4:56 PM, Christofer Bogaso
<bogaso.christofer at gmail.com> wrote:
> Dear all, can somebody please help me how to calculate "McFadden
> R-square" for a LOGIT model? Corresponding definition can be found
> here:
>
> http://publib.boulder.ibm.com/infocenter/spssstat/v20r0m0/index.jsp?topic=%2Fcom.ibm.spss.statistics.help%2Falg_plum_statistics_rsq_mcfadden.htm
>
>
> Here is my data:
>
> Data <- structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1,
> 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1,
> 0, 1, 1, 0, 1, 0, 47, 58, 82, 100, 222, 164, 161, 70, 219, 81,
> 209, 182, 185, 104, 126, 192, 95, 245, 97, 177, 125, 56, 85,
> 199, 298, 145, 78, 144, 178, 146, 132, 98, 120, 148, 123, 282,
> 79, 34, 104, 91, 199, 101, 109, 117, 1.1, 0.92, 1.72, 2.18, 1.75,
> 2.26, 2.07, 1.43, 1.92, 1.82, 2.34, 2.12, 1.81, 1.35, 1.26, 2.07,
> 2.04, 1.55, 1.89, 1.68, 0.76, 1.96, 1.29, 1.81, 1.72, 2.39, 1.68,
> 2.29, 2.34, 2.21, 1.42, 1.97, 2.12, 1.9, 1.15, 1.7, 1.24, 1.55,
> 2.04, 1.59, 2.07, 2, 1.84, 2.04, 51.2, 48.5, 50.8, 54.4, 52.4,
> 56.7, 54.6, 52.7, 52.3, 53, 55.4, 53.5, 51.6, 48.5, 49.3, 53.9,
> 55.7, 51.2, 54, 52.2, 51.1, 54, 55, 52.9, 53.7, 55.8, 50.4, 58.8,
> 54.5, 53.5, 48.8, 54.5, 52.1, 56, 56.2, 53.3, 50.9, 53.2, 51.7,
> 54.3, 53.7, 54.7, 47, 56.9, 0.321, 0.224, 0.127, 0.063, 0.021,
> 0.027, 0.139, 0.218, 0.008, 0.012, 0.076, 0.299, 0.04, 0.069,
> 0.33, 0.017, 0.166, 0.003, 0.01, 0.076, 0.454, 0.032, 0.266,
> 0.018, 0.038, 0.067, 0.075, 0.064, 0.065, 0.065, 0.09, 0.016,
> 0.061, 0.019, 0.389, 0.037, 0.161, 0.127, 0.017, 0.222, 0.026,
> 0.012, 0.057, 0.022, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1,
> 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1,
> 0, 1, 1, 0, 1, 0, 0, 1, 0), .Dim = c(44L, 6L), .Dimnames = list(
>    c("Obs 1", "Obs 2", "Obs 3", "Obs 4", "Obs 5", "Obs 6", "Obs 7",
>    "Obs 8", "Obs 9", "Obs 10", "Obs 11", "Obs 12", "Obs 13",
>    "Obs 14", "Obs 15", "Obs 16", "Obs 17", "Obs 18", "Obs 19",
>    "Obs 20", "Obs 21", "Obs 22", "Obs 23", "Obs 24", "Obs 25",
>    "Obs 26", "Obs 27", "Obs 28", "Obs 29", "Obs 30", "Obs 31",
>    "Obs 32", "Obs 33", "Obs 34", "Obs 35", "Obs 36", "Obs 37",
>    "Obs 38", "Obs 39", "Obs 40", "Obs 41", "Obs 42", "Obs 43",
>    "Obs 44"), c("Y", "X 1", "X 2", "X 3", "X 4", "X 5")))
>
>
> AND, my model is:
>
> glm(Data[,1] ~ Data[,-1], binomial(link = logit))
>
> Thanks,