Code:
. search table1_mc
Code:
. sysuse auto, clear . generate much_headroom = (headroom>=3) . table1_mc, by(foreign) vars(weight contn %5.0f \ price contln %5.0f %4.2f \ mpg conts %5.0f \ rep78 cate \ much_headroom bin) onecol test statistic +--------------------------------------------+ | factor N_0 N_1 m_0 m_1 | |--------------------------------------------| | Weight (lbs.) 52 22 0 0 | |--------------------------------------------| | Price 52 22 0 0 | |--------------------------------------------| | Mileage (mpg) 52 22 0 0 | |--------------------------------------------| | Repair record 1978 48 21 4 1 | |--------------------------------------------| | much_headroom 52 22 0 0 | +--------------------------------------------+ N_ ... #records used below, m_ ... #records not used +----------------------------------------------------------------------------------------------------------+ | Domestic Foreign Test Statistic p-value | |----------------------------------------------------------------------------------------------------------| | N=52 N=22 | |----------------------------------------------------------------------------------------------------------| | Weight (lbs.) 3317 (695) 2316 (433) Ind. t test t(72)= 6.25 <0.001 | |----------------------------------------------------------------------------------------------------------| | Price 5534 (×/1.50) 5959 (×/1.44) Ind. t test, logged data t(72)= -0.74 0.46 | |----------------------------------------------------------------------------------------------------------| | Mileage (mpg) 19 (17-22) 25 (21-28) Wilcoxon rank-sum Z= -3.10 0.002 | |----------------------------------------------------------------------------------------------------------| | Repair record 1978 Fisher's exact N/A <0.001 | | 1 2 ( 4%) 0 ( 0%) | | 2 8 (17%) 0 ( 0%) | | 3 27 (56%) 3 (14%) | | 4 9 (19%) 9 (43%) | | 5 2 ( 4%) 9 (43%) | |----------------------------------------------------------------------------------------------------------| | much_headroom 35 (67%) 8 (36%) Chi-square Chi2(1)= 6.08 0.014 | +----------------------------------------------------------------------------------------------------------+ Data are presented as mean (SD) or geometric mean (×/geometric SD) or median (IQR) for continuous measures, and n (%) for categorical measures.
0 Response to table1_mc can now also report the value of the test statistic
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