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From |
Nick Cox <n.j.cox@durham.ac.uk> |

To |
"'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: pweights in xtiles command are doing the opposite of what I expect them to do |

Date |
Wed, 2 Feb 2011 11:33:38 +0000 |

Interesting use of words. !!! Warning. The remainder of this post may strike you as highly pedantic or picky. Bail out now if you have an aversion to such a tone. !!! What you say sounds more like bias than skew. In recent months I have noted many people using "skewed" to mean "biased" in statistical contexts. As a conservative (linguistically), I think it's unfortunate if a very good word with an established statistical meaning is being watered down. Otherwise put, bias is a difference or shift in level (away from "true" values) and skew a shift in shape (away from symmetric distributions). (The two are not exclusive in practice, naturally.) Nick n.j.cox@durham.ac.uk Michael Boehm Steve, Thanks for this nonetheless. Using your example data I figured out that Stata was doing the "right" thing. The problem was that, adjusting for response rates in follow up surveys, ELS does in fact have a sample that is skewed towards individuals who are higher up the test score distribution in the population. Therefore, the results that Stata produces are correct. Thanks a lot for that again, Michael On Wed, Feb 2, 2011 at 4:22 AM, Steven Samuels <sjsamuels@gmail.com> wrote: > Sorry, my example didn't represent your data, where the lower ranking group > has the smaller weight. > On Feb 1, 2011, at 10:02 AM, Michael Boehm wrote: > I am trying to compute students' quantiles in the cognitive skill > distribution using their test results reported in a survey, the > Educational Longitudinal Study (ELS). The ELS oversamples individuals > who are of less privileged social background, which comes with lower > test scores. Therefore, individuals should be higher up in the skill > distribution within the sample than compared to the whole population. > If I adjust for the survey design, using the inverse probability of > being selected for the survey, I however get the opposite result. For > example, I would expect the mean of centil to be below centil1 and > below 50. > > xtile centil = F1TXMSTD if G12COHRT != 0 [pweight = F2F1WT], nq(100) > xtile centil1 = F1TXMSTD if G12COHRT != 0 & F2F1WT != 0 , nq(100) > > summarize centil centil1 > > Variable | Obs Mean Std. Dev. Min Max > -------------+-------------------------------------------------------- > centil | 12011 53.20806 28.94271 1 100 > centil1 | 12011 50.48081 28.86572 1 100 > > What am I doing wrong here? * * 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**:**st: pweights in xtiles command are doing the opposite of what I expect them to do***From:*Michael Boehm <michael.boehm1@gmail.com>

**Re: st: pweights in xtiles command are doing the opposite of what I expect them to do***From:*Steven Samuels <sjsamuels@gmail.com>

**Re: st: pweights in xtiles command are doing the opposite of what I expect them to do***From:*Michael Boehm <michael.boehm1@gmail.com>

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