Capture p-values from regression results

[tom sk]

Hi,

Im running Carhart 4 factor model and Im trying to create new variables contain coefficients for the factors, standard errors and p values for the factors from regression results, so far I was able to capture the slope coefficients and standard error by -_b[factor1]- and -_se[factor1]-, However, I couldn't find a command that can capture the p-values.

Any help is appreciated
Cheers,
Tom

[Attaullah Shah]

There are no stored results for p-values after regress command. You can obtain p-values using something like

local t = _b[_cons]/_se[_cons]
local p =2*ttail(e(df_r),abs(`t'))

You can replace _b[cons] with _b[variable_name] which you actually use in your regression.

[tom sk]

Thanks Attaullah

[Rich Goldstein]

actually, here Attaullah is not correct; look at "r(table)" (part of "return list") after estimating your regression and you will see the p-values as part of the matrix of results

[Attaullah Shah]

What i actually meant that in standard regression, the p-values cannot be seperaterly obtained through return list, yes it is in matrix, but you have to do additional tricks to seperate it from the matrix table.

[An Dao]

Dear Statalists,
Capture p-values from zero inflated regression results

I would like to capture p values from zero inflated model. However, the results of the zinb model are displayed in two componets; the count and the inflated components. Each of these results has its own p value. Therefore, the following commands seem did not get through (when display p-values, they are all missing). Please give your advice on how to capture p-value for each component? Thank you.


// fitting zero inflated model

zinb fiveyoddmfs SES4, inflate(SES4) level(97.5)

// Calculation of t-value and p-value
local t = _b[SES4] / _se[SES4]
local p = 2 * ttail(e(df_r), abs(`t'))

// Displaying the p-value
display "P-value for SES4: " %8.4f `p'


CODE
clear
input byte fiveyoddmfs float SES4
. -5.300604
. 4.120511
0 .3542542
0 4.7029696
0 -3.051065
. -.6050887
. 1.3122363
. -3.945837
0 5.222175
. -3.770617
. .
. -2.95614
. -2.1549318
. -1.8057196
6 3.7224984
. -1.3404984
. -2.700492
. 3.407414
. .
. .
. 1.185773
. -5.068585
1 2.89098
. .
. 1.494044
0 1.8064017
. 1.6100533
. 1.9896634
2 3.118999
0 .
0 -2.3078828
. .
. 3.743583
. .
. -2.8125024
. .
0 2.664365
0 2.1556137
1 -3.484615
0 .
. .
. -.8042078
0 .
. .
. -8.238112
0 2.557625
. 3.182209
0 .7825772
. 1.440104
. 1.826258
end
[/CODE]