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-------------------------------------------------------------------------------- I'm hoping for some help in interpreting the Wald Chi2 statistic output for -xtgee- models. Below is a longish description of my question. Thanks in advance for any insight, or direction to the relevant resources/references ... I've checked the Stata manuals, and have come up dry. I know that chi2 is a goodness of fit measure (and it's significant in all my models). Below I give you output (headers only) from 5 models: 1 x controls, 3 x controls plus a single I.V., and 1 x full model. The models show "(22)" after the chi2 stat, which I take to be the d.f. Now, two things are puzzling: 1) it seems that the d.f. is based on inter-year periods and not variables in the model. there are 21 interyear periods but 25 variables in my models ... So is the chi2 a measure of the variation from period to period?? You would expect a chi2 squared stat to compare to the difference in two distributions, so maybe that's how to interpret it ... the inter-period differences across the sample? Is this right?? 2) I'm getting HUGE differences in the values: a) control: 227.98 b) control + one I.V. (ie., 3 different models): 227.98, 323.79, 2035.13 c) Full Model (controls and all 3 I.V.s): 692.60 What do I make of this? While I would expect, of course, some improvement in model fit with addition of the I.V.s, is it "reasonable" to have the chi2 jumping around this much?? All I'm adding is one variable in each case (except, of course, the full model). OUTPUT: a) CONTROL ONLY: . xtgee PerYEInnTr AttendL PerMSTrade NPitch pitchpark_C year1969-year1988 if e(sample), i(adj_teamno) t(year) corr(ar5) robust GEE population-averaged model Number of obs = 496 Group and time vars: adj_teamno year Number of groups = 24 Link: identity Obs per group: min = 13 Family: Gaussian avg = 20.7 Correlation: AR(5) max = 21 Wald chi2(22) = 227.98 Scale parameter: .011506 Prob > chi2 = 0.0000 b) CONTROL + PerInc_67L I.V.: . xtgee PerYEInnTr PerInc_67L AttendL PerMSTrade NPitch pitchpark_C year1969-year1988, i(adj_teamno) t(year) corr(ar5) robust GEE population-averaged model Number of obs = 496 Group and time vars: adj_teamno year Number of groups = 24 Link: identity Obs per group: min = 13 Family: Gaussian avg = 20.7 Correlation: AR(5) max = 21 Wald chi2(22) = 323.79 Scale parameter: .0113685 Prob > chi2 = 0.0000 c) CONTROL + t_w_pct I.V.: xtgee PerYEInnTr t_w_pct AttendL PerMSTrade NPitch pitchpark_C year1969-year1988 if e(sample), i(adj_teamno) t(year) corr(ar5) robust GEE population-averaged model Number of obs = 496 Group and time vars: adj_teamno year Number of groups = 24 Link: identity Obs per group: min = 13 Family: Gaussian avg = 20.7 Correlation: AR(5) max = 21 Wald chi2(22) = 2035.13 Scale parameter: .0112536 Prob > chi2 = 0.0000 d)CONTROL + PostFA I.V.: xtgee PerYEInnTr PostFA AttendL PerMSTrade NPitch pitchpark_C year1969-year1988 if e(sample), i(adj_teamno) t(year) corr(ar5) robust note: year1976 dropped due to collinearity GEE population-averaged model Number of obs = 496 Group and time vars: adj_teamno year Number of groups = 24 Link: identity Obs per group: min = 13 Family: Gaussian avg = 20.7 Correlation: AR(5) max = 21 Wald chi2(22) = 227.98 Scale parameter: .011506 Prob > chi2 = 0.0000 e) FULL MODEL: xtgee PerYEInnTr t_w_pct PostFA PerInc_67L AttendL PerMSTrade NPitch pitchpark_C year1969-year1988 if e(sample), i(adj_teamno) t(year) corr(ar5) robust note: year1976 dropped due to collinearity GEE population-averaged model Number of obs = 496 Group and time vars: adj_teamno year Number of groups = 24 Link: identity Obs per group: min = 13 Family: Gaussian avg = 20.7 Correlation: AR(5) max = 21 Wald chi2(22) = 692.60 Scale parameter: .0111595 Prob > chi2 = 0.0000 ***************************************** Thomas P. Moliterno Graduate School of Management University of California, Irvine tmoliter@uci.edu www.gsm.uci.edu/~tmoliter ***************************************** * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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