[R] rms package: output interpretation
dwinsemius at comcast.net
Fri Mar 25 18:03:19 CET 2016
> On Mar 25, 2016, at 6:31 AM, T.Riedle <tr206 at kent.ac.uk> wrote:
> Hi everybody,
> I am trying to run a logistic regression using the rms package. Here is the output of my model.
> Logistic Regression Model
> lrm(formula = stock.market.crash ~ crash.t.1.to.t.L + MA.inflator.monthly +
> realized.volatility.10 + MA.MP.100 + MA.UI.100 + MA.DEI.100 +
> MA.UPR.100, data = FDL.model_monthly)
> Model Likelihood Discrimination Rank Discrim.
> Ratio Test Indexes Indexes
> Obs 45 LR chi2 21.57 R2 0.529 C 0.889
> 0 30 d.f. 7 g 2.789 Dxy 0.778
> 1 15 Pr(> chi2) 0.0030 gr 16.267 gamma 0.778
> max |deriv| 6e-06 gp 0.340 tau-a 0.354
> Brier 0.131
> Coef S.E. Wald Z Pr(>|Z|)
> Intercept -11.6543 5.9683 -1.95 0.0509
> crash.t.1.to.t.L -4.5335 2.5705 -1.76 0.0778
> MA.inflator.monthly -2.4400 1.2735 -1.92 0.0554
> realized.volatility.10 24.7952 10.3298 2.40 0.0164
> MA.MP.100 6.9404 4.1511 1.67 0.0945
> MA.UI.100 -125.7101 54.5219 -2.31 0.0211
> MA.DEI.100 519.9589 255.0241 2.04 0.0415
> MA.UPR.100 2.6938 2.2209 1.21 0.2252
> I am a bit confused regarding the interpretation of the chi2 and its p-value. Can anybody help me interpret the results?
I don't think anyone can help you unless you first describe the structure of the data. I worry that you are analyzing some sort of panel structure and have not yet accounted for autocorrelation in monthly measures.
> I get a high R2 but chi2 seems to be significant and high. How do I interpret these results in the rms package?
This suggests you need to talk to someone with deeper statistical background, and that's not really what r-help bills itself as providing. Is this part of an education experience or task? Do you have a supervisor that could be consulted?
Alameda, CA, USA
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