Dear all
I am trying to create a table that contains summary statistics with chi2 and t-test.
I tried both asdoc and eststo/ estpost commands, but I still do not succeed to produce the tab I would like.
With eststo/ estpost I tried the following
With asdoc I like the possibility of using i.var in my descriptive statistics. Anyway I was not able to insert a new column with the statistical tests
In the command above there is an error for sure.
I would like to have a table like this and in addition have the sd in parentheses below the mean and the stars in the statistical test
here an example of my data
I am trying to create a table that contains summary statistics with chi2 and t-test.
I tried both asdoc and eststo/ estpost commands, but I still do not succeed to produce the tab I would like.
With eststo/ estpost I tried the following
Code:
eststo clear
eststo old: qui estpost sum gender age career_path farm_size farm_typology acquire_old farm_turnover if survey == 1
eststo young: qui estpost sum gender age career_path farm_size farm_typology acquire_old farm_turnover if survey ==0
* this is for continuous variables (I have more in my sample)
local var1 age farm_turnover
eststo test1: qui estpost ttest `var1', by(survey) unequal
local var2 gender career_path farm_size farm_typology acquire_old
eststo test2: qui estpost tab `var2' survey, chi2
local pval1= e(p)
mat define pval=(`pval1', `pval2')
*here I would need a matrix that save all the pvalues in test2
mat colnames pval= "`varname’"
estadd matrix pval= pval
estimates store pval_test2
tab `vars' survey, chi2eststo ttest: qui estpost ttest price mpg, by(foreign) unequal
esttab old young test1 test2, replace star(* 0.10 ** 0.05 *** 0.01) nonumber noobs label ///
alignment(rrrr) ///
cells("count(pattern(1 1 0 0) fmt(0)) mean(pattern(1 1 0 0) fmt(2)) b(star pattern(0 0 1 0) fmt(2)) pval(star pval(pval) pattern(0 0 0 1) fmt(3)) ") ///
mtitle("Old" "Young" "ttest" "Chi2") ///
collabels("N" "Mean" "Mean Diff." "p-value")
Code:
global var i.gender age career_path i.farm_size i.farm_typology i.acquire_old farm_turnover row( \i, \i, Old, \i, \i, Young,\i) replace asdoc, row( N, Mean, SD, N, Mean, SD) bys survey: sum $var, label save(file3) replace dec(2) asdoc, accum(`r(N)', `r(mean)', `r(sd)') tabulate $var survey, chi2 asdoc, accum(`r(chi2)' `r(p)') asdoc, row( `var’, $accum)
I would like to have a table like this and in addition have the sd in parentheses below the mean and the stars in the statistical test
| Variable | Old | Young | Total | mean diff | ||||
| Obs | Mean (sd) | Obs. | Mean (sd) | Obs |
|
|||
| Gender | . | . | . | . | . | |||
| Male | ||||||||
| Female | ||||||||
| Age of the interviewed | ||||||||
| Early involvement in agriculture | ||||||||
| Farm size | ||||||||
| Small farms: EUR 2 000 – < EUR 8 | ||||||||
| Medium-sized farms: EUR 8 000 – | ||||||||
| Large farms: EUR 25 000 – < EUR | ||||||||
| Very large farms: ≥ EUR 100 000 | ||||||||
| Farm typology | ||||||||
| Innovator | ||||||||
| Diversifier | ||||||||
| Environmentalist | ||||||||
| Traditionalist | ||||||||
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input byte gender float(age career_path farm_size farm_typology acquire_old farm_turnover) 1 57 0 1 4 1 7000 0 58 0 3 4 1 50000 0 56 1 4 3 1 200000 0 63 0 3 2 2 61000 0 67 0 3 4 2 40000 0 60 0 4 3 1 230000 0 65 0 4 4 1 100000 0 75 0 2 2 1 15000 0 59 1 3 4 1 85000 0 66 0 3 2 1 40000 0 56 0 2 2 1 10000 0 56 0 3 2 1 35000 0 59 1 3 4 1 55000 1 57 0 3 2 1 40000 0 68 0 4 1 1 130000 0 62 0 3 1 1 30000 0 72 0 2 1 1 20000 0 75 0 2 4 2 10000 0 61 0 3 1 1 50000 1 56 0 3 4 1 75000 1 64 1 2 3 2 20000 0 56 0 3 4 1 50000 0 66 0 3 4 2 75000 0 61 0 3 2 1 70000 0 59 0 4 2 1 120000 0 59 1 3 3 1 70000 0 73 1 4 2 2 180000 0 62 0 2 4 1 10000 1 58 0 3 2 1 55000 0 58 1 4 3 1 240000 0 69 0 3 4 1 30000 0 56 0 3 4 1 50000 1 60 0 3 4 1 54300 0 66 0 2 2 1 20000 1 61 0 3 4 1 30000 1 65 0 2 2 1 10000 0 66 1 3 4 1 65000 0 72 0 4 3 2 110000 0 63 0 3 4 2 90000 0 68 0 3 1 1 90000 1 68 0 2 2 1 10000 0 58 0 1 1 1 5000 0 67 1 4 3 2 110000 1 57 0 3 4 1 60000 0 57 0 4 4 1 150000 0 68 0 4 3 1 100000 0 70 1 3 4 2 70000 1 81 0 3 2 1 95000 0 65 0 1 2 2 6000 0 63 1 3 3 2 90000 0 70 1 3 3 1 70000 0 56 0 4 4 1 135000 1 56 0 4 2 1 106000 0 57 0 2 2 1 15000 0 61 0 3 3 1 70000 0 62 0 4 4 1 100000 0 64 0 2 1 1 8000 0 57 1 4 3 1 650000 1 58 0 3 1 1 50000 1 60 0 3 4 1 65000 0 61 0 3 4 1 35000 0 65 0 2 2 1 8000 0 73 1 4 2 1 160000 0 67 1 4 3 1 180000 1 56 0 2 4 1 20000 0 70 0 3 2 1 65000 0 56 0 2 2 1 15000 0 59 0 3 2 1 30000 0 66 0 2 4 1 10000 0 66 0 4 3 1 110000 0 63 0 3 2 2 32000 0 66 1 4 3 2 120000 1 56 0 2 2 1 13000 0 71 1 3 3 2 70000 0 69 0 4 3 2 100000 0 60 0 2 4 1 15000 0 60 1 4 3 1 230000 0 58 0 2 2 1 20000 0 71 0 3 3 1 90000 0 56 0 3 4 1 30000 0 57 0 3 2 1 30000 1 61 0 2 4 1 20000 0 74 1 3 3 1 75000 1 56 0 2 2 1 20000 0 72 0 3 4 1 30000 0 66 0 2 4 1 24000 0 70 0 3 4 1 65000 0 67 0 4 3 2 140000 0 61 0 3 3 1 28000 0 58 0 3 1 1 60000 0 65 0 3 2 1 30000 0 56 0 3 2 1 30000 1 61 0 1 1 1 5000 1 59 0 2 2 1 10000 1 59 1 3 4 1 60000 0 59 1 4 2 2 190000 0 63 1 3 3 2 75000 0 63 0 3 2 1 75000 0 71 1 3 3 2 75000 1 65 0 1 4 1 6000 end label values gender gender label def gender 0 "Male", modify label def gender 1 "Female", modify label values farm_size farmsize label def farmsize 1 "Small farms: EUR 2 000 – < EUR 8 000", modify label def farmsize 2 "Medium-sized farms: EUR 8 000 – < EUR 25 000", modify label def farmsize 3 "Large farms: EUR 25 000 – < EUR 100 000", modify label def farmsize 4 "Very large farms: ≥ EUR 100 000", modify label values farm_typology farm_typology label def farm_typology 1 "Innovator", modify label def farm_typology 2 "Diversifier", modify label def farm_typology 3 "Environmentalist", modify label def farm_typology 4 "Traditionalist", modify label values acquire_old acq_1 label def acq_1 1 "Inherited or donated", modify label def acq_1 2 "Entirely or partially bought/rented", modify
