Recently, I'm conducting research, we would like to see some difference between different national identity groups. First, I applied One-way ANOVA (oneway) command to test the mean comparison among identity groups. But when I test it with pwmean command, the results changed. Does anyone know the reason and the difference between those two commands?
oneway polsati newnid5, bonferroni tabulate
new coded |
national | Summary of political satisfactory
identity | Mean Std. Dev. Freq.
------------+------------------------------------
1 | 4 1 198
2 | 4 1 115
3 | 4 1 448
4 | 4 1 50
5 | 4 1 124
------------+------------------------------------
Total | 4 1 935
Analysis of Variance
Source SS df MS F Prob > F
------------------------------------------------------------------------
Between groups 29.9813114 4 7.49532785 8.25 0.0000
Within groups 844.664678 930 .908241589
------------------------------------------------------------------------
Total 874.645989 934 .936451809
Bartlett's test for equal variances: chi2(4) = 33.8585 Prob>chi2 = 0.000
Comparison of political satisfactory by new coded national identity
(Bonferroni)
Row Mean-|
Col Mean | 1 2 3 4
---------+--------------------------------------------
2 | -0
| 1.000
|
3 | -0 -0
| 0.000 0.219
|
4 | -0 -0 -0
| 0.010 0.202 1.000
|
5 | -1 -0 -0 -0
| 0.000 0.015 0.908 1.000
Then, I tried pwmean to see the mean comparison, but I got the different answer like below:
. pwmean polsati, over(newnid5) mcompare(bonferroni) cieffects pveffects effects cimeans
Pairwise comparisons of means with equal variances
over : newnid5
--------------------------------------------------------------
| Unadjusted
polsati | Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
newnid5 |
1 | 4.419192 .067728 4.286275 4.552109
2 | 4.295652 .0888693 4.121245 4.47006
3 | 4.066964 .0450258 3.9786 4.155328
4 | 3.92 .134777 3.655498 4.184502
5 | 3.903226 .0855835 3.735267 4.071185
--------------------------------------------------------------
---------------------------
| Number of
| Comparisons
-------------+-------------
newnid5 | 10
---------------------------
-----------------------------------------------------
| Bonferroni
polsati | Contrast Std. Err. t P>|t|
-------------+---------------------------------------
newnid5 |
2 vs 1 | -.1235397 .1117355 -1.11 1.000
3 vs 1 | -.3522276 .081329 -4.33 0.000
4 vs 1 | -.4991919 .1508374 -3.31 0.010
5 vs 1 | -.5159661 .1091403 -4.73 0.000
3 vs 2 | -.2286879 .0996247 -2.30 0.219
4 vs 2 | -.3756522 .1614391 -2.33 0.202
5 vs 2 | -.3924264 .1233786 -3.18 0.015
4 vs 3 | -.1469643 .1420991 -1.03 1.000
5 vs 3 | -.1637385 .096705 -1.69 0.908
5 vs 4 | -.0167742 .1596539 -0.11 1.000
-----------------------------------------------------
even the mean of each identity groups are different in these two commands. Does anyone know how to deal with it? Thanks!
Related Posts with Question on oneway anova and pairwise comparison
DMARIANO in stata: Diebold_Mariano test: basic questiondmariano (written by Christopher Baum; ssc install dmariano) performs the Diebold_Mariano test for p…
Creating lags of many variables all at onceHow can I efficiently create new variables for lags of many variables in my dataset? Say for example…
esttab? Hi, I have 4 groups of individuals and I want to analyze if there are differences for a long list o…
Testing the difference between mediansHi, I have two groups. One group watches a median of 4 hours of TV per day. The other group watches…
Identifying differences in a variable within a datasetI have a dataset that has data that is pooled across different years. At the moment, I would to lik…
Subscribe to:
Post Comments (Atom)
0 Response to Question on oneway anova and pairwise comparison
Post a Comment