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st: Comparing 2 models with -test- command under SVY
Hello Statalist-ers,
About a year ago there was a post about comparing nested models (one with an interaction term and one without an interaction term) while using survey data and the woman who posted was told to use the -test- command and was provided code by Maarten in which he instructed her to force the coefficients of the interaction terms to be equal to 0.
I now have the exact same problem as the previous poster but I can't seem to translate the sample code to work with my data (this is the link to that post http://www.stata.com/statalist/archive/2008-11/msg01123.html and text is also posted below). I have categorical*categorical interaction terms and I'm not sure if that is part of the problem. Each term entering into the interaction terms has 4 or 5 categories so when I run my model it looks like this:
. xi3: svy: logistic stigma_yn i.age5*i.raceth i.union i.ieduc i.povcat3 i.ireligion
> i.itimeinUS i.insurance i.region
i.age5 _Iage5_1-5 (naturally coded; _Iage5_1 omitted)
i.raceth _Iraceth_1-4 (naturally coded; _Iraceth_1 omitted)
i.union _Iunion_1-4 (naturally coded; _Iunion_1 omitted)
i.ieduc _Iieduc_1-4 (naturally coded; _Iieduc_1 omitted)
i.povcat3 _Ipovcat3_1-3 (naturally coded; _Ipovcat3_1 omitted)
i.ireligion _Iireligion_1-4 (naturally coded; _Iireligion_1 omitted)
i.itimeinUS _IitimeinUS_0-3 (naturally coded; _IitimeinUS_0 omitted)
i.insurance _Iinsurance_0-4 (naturally coded; _Iinsurance_0 omitted)
i.region _Iregion_1-4 (naturally coded; _Iregion_1 omitted)
(running logistic on estimation sample)
Survey: Logistic regression
Number of strata = 7 Number of obs = 4146
Number of PSUs = 93 Population size = 4125.8935
Design df = 86
F( 40, 47) = 4.91
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
stigma_yn | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Iage5_2 | .6519237 .1351332 -2.06 0.042 .4317562 .9843623
_Iage5_3 | .791465 .1644478 -1.13 0.263 .5236584 1.196232
_Iage5_4 | .6950092 .2020618 -1.25 0.214 .3899302 1.23878
_Iage5_5 | .5621536 .1438475 -2.25 0.027 .3380148 .9349197
_Iraceth_2 | .27729 .067397 -5.28 0.000 .1710378 .4495483
_Iraceth_3 | .6354438 .1837908 -1.57 0.121 .3575765 1.129238
_Iraceth_4 | 1.522723 .6657219 0.96 0.339 .638516 3.631365
_Iag2Xra2 | 1.892653 .5600417 2.16 0.034 1.051002 3.408306
_Iag2Xra3 | 1.239234 .4250937 0.63 0.533 .6266131 2.450797
_Iag2Xra4 | .5200602 .2612843 -1.30 0.197 .1915566 1.41192
_Iag3Xra2 | 1.067876 .3455609 0.20 0.840 .5612341 2.031877
_Iag3Xra3 | .9946504 .2931404 -0.02 0.986 .5536393 1.786957
_Iag3Xra4 | .3279903 .1664101 -2.20 0.031 .1196272 .8992742
_Iag4Xra2 | .9478445 .3612668 -0.14 0.889 .4442991 2.022082
_Iag4Xra3 | 1.038767 .530176 0.07 0.941 .3765942 2.86525
_Iag4Xra4 | .2598451 .148765 -2.35 0.021 .0832598 .8109497
_Iag5Xra2 | 1.751892 .7131544 1.38 0.172 .7799346 3.935107
_Iag5Xra3 | 1.009418 .3768195 0.03 0.980 .4805957 2.12013
_Iag5Xra4 | .5243718 .2864595 -1.18 0.241 .1770108 1.553384
_Iunion_2 | 1.231949 .1559979 1.65 0.103 .9577888 1.584587
_Iunion_3 | 1.21506 .1594978 1.48 0.141 .9359836 1.577347
_Iunion_4 | 1.521763 .2374102 2.69 0.009 1.115978 2.075095
_Iieduc_2 | 1.192253 .1610352 1.30 0.196 .911502 1.559478
_Iieduc_3 | 1.412647 .1853921 2.63 0.010 1.088253 1.833738
_Iieduc_4 | 1.539768 .2867434 2.32 0.023 1.063355 2.229629
_Ipovcat3_2 | .8198406 .0721716 -2.26 0.027 .6882208 .9766324
_Ipovcat3_3 | .994166 .1061167 -0.05 0.956 .8040916 1.229171
_Iireligio~2 | 1.195083 .117494 1.81 0.073 .9829202 1.453041
_Iireligio~3 | 1.079557 .1290552 0.64 0.524 .8512099 1.36916
_Iireligio~4 | 1.013235 .1638016 0.08 0.935 .7347503 1.397272
_IitimeinU~1 | 1.074207 .1776751 0.43 0.666 .7731953 1.492406
_IitimeinU~2 | 1.644738 .2959388 2.77 0.007 1.150148 2.352012
_IitimeinU~3 | .8671913 .2087065 -0.59 0.555 .5374439 1.399254
_Iinsuranc~1 | .8847986 .1607652 -0.67 0.502 .6165618 1.269733
_Iinsuranc~2 | 1.202234 .1829168 1.21 0.229 .888449 1.626841
_Iinsuranc~3 | .7540169 .1588092 -1.34 0.184 .4960719 1.146087
_Iinsuranc~4 | 1.095395 .1789676 0.56 0.579 .7916176 1.515746
_Iregion_2 | 1.651972 .3725572 2.23 0.029 1.05511 2.58647
_Iregion_3 | 1.534596 .2128685 3.09 0.003 1.16476 2.021864
_Iregion_4 | 1.545248 .2389391 2.81 0.006 1.136319 2.101341
------------------------------------------------------------------------------
Note: variance scaled to handle strata with a single sampling unit.
I want to compare this model with a model without the interaction term...Can anyone help me understand how to how to compare the two models? I tried using the -test- command after running the model that includes the interaction term and forcing the coefficients of the interaction terms to =0 but it didn't work. Also, there are so many interaction terms b/c of all the dummy variables that it just seems like a big mess!!
Any help would be greatly appreciated!
Thanks,
Kristen
*****************PREVIOUS POST that I refer to above*******************
Re: st: testing for interactions: svy models