# Re: st: Stanard Error for Difference in Difference cross-tabulation

 From Richard Palmer-Jones 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
> 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
>>  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
>>>
>>> While I agree with  Maarten about the analysis procedure, I am unclear
>>> 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
>
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```