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From |
Richard Palmer-Jones <richard.palmerjones@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Stanard Error for Difference in Difference cross-tabulation |

Date |
Thu, 12 Feb 2009 20:40:13 +0000 |

Dear Steve and others It is a DHS survey from Measuredhs. I will be using svy: commands in due course - I am trying to get my ideas straight first. The survey variables are usually common svy: v001 [weight=v005], strata(v024) // usually, though weights vary with statistics svy: reg ....... // as before ? Richard On Thu, Feb 12, 2009 at 2:45 PM, Steven Samuels <sjhsamuels@earthlink.net> wrote: > 0.503 looks like the right number Richard. But I'd like to know more: What > was the study design which gave 2,698 observations in 1999? If it is sample > survey, you should be using Stata's survey commands. > > > -Steve > On Feb 12, 2009, at 6:27 AM, Richard Palmer-Jones wrote: > >> Thanks for the replies, and sorry not to have been clearer and the >> delay in responding (student strike!) >> >> the variables are: >> label yearsedn "years of education" // cross section in 1999 >> gen old = born >= 1956 & born <= 1961 >> gen young = born >- 1970 & born <= 1975 >> gen highintensity = state >= 5 & state <= 19 // states 1 -4 = low >> intensity >> label highintensity "high primary school funding in 1976-81" // (i.e. >> treated) >> gen young_high = highintensity * young >> >> * Maarten suggests >> . reg yearsedn young highintensity young_high if young | old >> >> Source | SS df MS Number of obs = >> 2698 >> -------------+------------------------------ F( 3, 2694) = >> 115.81 >> Model | 8584.36711 3 2861.4557 Prob > F = >> 0.0000 >> Residual | 66562.2808 2694 24.7076024 R-squared = >> 0.1142 >> -------------+------------------------------ Adj R-squared = >> 0.1132 >> Total | 75146.6479 2697 27.8630508 Root MSE = >> 4.9707 >> >> >> ------------------------------------------------------------------------------ >> yearsedn | Coef. Std. Err. t P>|t| [95% Conf. >> Interval] >> >> -------------+---------------------------------------------------------------- >> young | 2.286417 .4506203 5.07 0.000 1.40282 >> 3.170013 >> highintens~y | -3.533677 .3945928 -8.96 0.000 -4.307412 >> -2.759941 >> young_high | .7222411 .503475 1.43 0.152 -.2649952 >> 1.709477 >> _cons | 6.118812 .3497354 17.50 0.000 5.433035 >> 6.804589 >> >> ------------------------------------------------------------------------------ >> >> I want a table with mean and standard errors of years of education >> where the Xs are in the following table, and the marginal differences >> >> young >> 0 1 difference >> _______________________________________ >> lo | X | X | X >> high | X | X | X >> _______________________________________ >> difference | X | X | X >> >> The row and column Xs can be filled in from calcuations of means (e.g >> in ttest), except for the bottom right X >> >> Maarten's suggestion is that the appropriate se is 0.503 >> >> Thanks for further help >> >> RIchard >> >> >> >> >> >> On Tue, Feb 10, 2009 at 5:18 PM, Steven Samuels >> <sjhsamuels@earthlink.net> wrote: >>> >>> While I agree with Maarten about the analysis procedure, I am unclear >>> about >>> the design- does "one of which" in your description refer to region or >>> to >>> cohort? Was there a treated cohort and a non-treated cohort within each >>> region? Or, were there two cohorts within each region, but with treatment >>> differing between region? Do you have a before/after differences , or >>> are >>> all comparisons cross-sectional? >>> >>> Please lay out in more detail the design of the study >>> >>> -Steve >>> >>>> >>>> --- On Tue, 10/2/09, Richard Palmer-Jones wrote: >>>>> >>>>> I want to calculate the standard error of the mean >>>>> "diffference in difference". I have samples from two >>>>> cohorts in each of two regions, one of which received >>>>> a treatment, and their respective years of education; >>>>> how to I calculate the standard error of the >>>>> difference in difference of the years of education? >>>> >>>> Looks to me like an interaction effect: >>>> The dummy for cohort tells you how much the average >>>> education differs over cohorts, and you think that >>>> this difference differs across regions, so the >>>> interaction effect between cohort and region gives >>>> you this difference in difference, and -regress- will > > * > * 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: Stanard Error for Difference in Difference cross-tabulation***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: st: Stanard Error for Difference in Difference cross-tabulation***From:*Steven Samuels <sjhsamuels@earthlink.net>

**Re: st: Stanard Error for Difference in Difference cross-tabulation***From:*Richard Palmer-Jones <richard.palmerjones@gmail.com>

**Re: st: Stanard Error for Difference in Difference cross-tabulation***From:*Steven Samuels <sjhsamuels@earthlink.net>

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