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From |
Chao Yawo <Yawo1964@yahoo.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Treatment for Missing Values - What Options ? |

Date |
Wed, 15 Jul 2009 08:59:20 -0400 |

Maarten, thanks very much for your advice. It could to me to check one more thing, that most of the people who are missing on the condom use variable may be those who are not sexually active or have not reached sexual debut. so I created a new variable for condom use, assigning a value of 2 to those who are Missing (V6=761_Miss), and crosstabulated it the variable for those who are Sexually Active (V531_R), with the following results: . tabulate V536_R V761_Miss, column +-------------------+ | Key | |-------------------| | frequency | | column percentage | +-------------------+ | RECODE of V761_R (RECODE of V761 RECODE of V536 | (Last intercourse used condom (Recent sexual | (See also SMV761) activity) | Not Used Used Missing | Total ------------------+---------------------------------+---------- NotSexuallyActive | 0 0 2,146 | 2,146 | 0.00 0.00 59.40 | 20.06 ------------------+---------------------------------+---------- SexuallyActive | 6,012 1,075 1,467 | 8,554 | 100.00 100.00 40.60 | 79.94 ------------------+---------------------------------+---------- Total | 6,012 1,075 3,613 | 10,700 | 100.00 100.00 100.00 | 100.00 Given that close to 60% of those who are "Missing" on the condom use variable are not sexually active, I decided to condition / subset the check I did earlier for the relationship between the dependent variable and the Missing variable on only those who are Sexually Active, and got a different result from what I sent out yesterday: . logit mis V781_R [pweight=weight], cluster(psu), if V536_R==1 (sum of wgt is 8.8262e+03) Iteration 0: log pseudolikelihood = -3739.3157 Iteration 1: log pseudolikelihood = -3729.0254 Iteration 2: log pseudolikelihood = -3728.8988 Iteration 3: log pseudolikelihood = -3728.8988 Logistic regression Number of obs = 8436 Wald chi2(1) = 0.55 Prob > chi2 = 0.4590 Log pseudolikelihood = -3728.8988 Pseudo R2 = 0.0028 (Std. Err. adjusted for 357 clusters in psu) ------------------------------------------------------------------------------ | Robust mis | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- V781_R | .383671 .5181314 0.74 0.459 -.631848 1.39919 _cons | -1.695747 .1268113 -13.37 0.000 -1.944293 -1.447202 ------------------------------------------------------------------------------ Thus, if we take sexual activity only into consideration, the results are non-significant. Should I take this as evidence that the missing variable does not severely impact my DV? thx - cY On Wed, Jul 15, 2009 at 3:11 AM, Maarten buis<maartenbuis@yahoo.co.uk> wrote: > > --- On Tue, 14/7/09, Chao Yawo wrote: > >> Here is what i got when I run the >> suggested code, with a slight >> modification taking the survey design into account: > <snip> >> the significance mean then that the DV (V781_R) negatively >> predicts the missing value (mis). What does that mean? ... > > It means you are in trouble, or at least that the solution > was not as easy as we thought. Since you have quite a larger > proportion of missing cases and the probability of missingness > is quite strongly related to your dependent variable (an odds > ratio of exp(-.6133271)= .54), just ignoring these missing > values will influence your results. > > I would do a mixture of approaches and hope they lead to > similar conclusions. > > 1) I would do -ice- > > 2) You could use your faithfulness variable > > 3) use -ice- as in 1) but now estimate a model with multiple > risky behavior variables, and combine their effects in a > sheaf coefficient using -sheafcoef-. This way you could > diminish the influence of the imputing that many values > values on one of the indicator variables. > > You can download -sheafcoef- from SSC by typing in Stata > -ssc install sheafcoef-. There is a more extensive > discussion of this type of models in the helpfile of > -propcnsreg-, which can be downloaded by typing > -ssc install propcnsreg-. In order to use -sheafcoef- > you will need to specify the -storebv- option in -mim-. > > However, I would not do the dummy variable approach, for reason > already mentioned by Rich Goldstein and in an earlier post > by me: > http://www.stata.com/statalist/archive/2007-12/msg00030.html > > Hope this helps, > Maarten > > ----------------------------------------- > Maarten L. Buis > Institut fuer Soziologie > Universitaet Tuebingen > Wilhelmstrasse 36 > 72074 Tuebingen > Germany > > http://home.fsw.vu.nl/m.buis/ > ----------------------------------------- > > > > > * > * 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/ > * * 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/

**References**:**Re: st: Treatment for Missing Values - What Options ?***From:*Maarten buis <maartenbuis@yahoo.co.uk>

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