Skip to content

Instantly share code, notes, and snippets.

@puterleat

puterleat/gist:e7bc920b228207e8cff8

Created January 30, 2015 13:45
Show Gist options

  • Select an option

    Learn more about clone URLs
  • Save puterleat/e7bc920b228207e8cff8 to your computer and use it in GitHub Desktop.

Select an option

Learn more about clone URLs
Save puterleat/e7bc920b228207e8cff8 to your computer and use it in GitHub Desktop.
Download ZIP
Raw
gistfile1.txt
. xtmixed z_howstrong howmany || participant :
Performing EM optimization:
Performing gradient-based optimization:
Iteration 0: log likelihood = -530.88526
Iteration 1: log likelihood = -530.88526
Computing standard errors:
Mixed-effects ML regression Number of obs = 420
Group variable: participant Number of groups = 15
Obs per group: min = 28
avg = 28.0
max = 28
Wald chi2(1) = 86.49
Log likelihood = -530.88526 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
z_howstrong | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
howmany | .1919117 .0206352 9.30 0.000 .1514674 .232356
_cons | -.5300418 .21442 -2.47 0.013 -.9502973 -.1097863
------------------------------------------------------------------------------
------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
participant: Identity |
sd(_cons) | .7859034 .1604083 .5267846 1.172479
-----------------------------+------------------------------------------------
sd(Residual) | .8072407 .0284476 .7533664 .8649675
------------------------------------------------------------------------------
LR test vs. linear regression: chibar2(01) = 116.96 Prob >= chibar2 = 0.0000
. xtmixed z_howoftencr howmany || participant :
Performing EM optimization:
Performing gradient-based optimization:
Iteration 0: log likelihood = -496.45295
Iteration 1: log likelihood = -496.45295
Computing standard errors:
Mixed-effects ML regression Number of obs = 420
Group variable: participant Number of groups = 15
Obs per group: min = 28
avg = 28.0
max = 28
Wald chi2(1) = 144.54
Log likelihood = -496.45295 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
z_howoftencr | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
howmany | .2309645 .0192114 12.02 0.000 .1933109 .2686181
_cons | -.637902 .2384442 -2.68 0.007 -1.105244 -.17056
------------------------------------------------------------------------------
------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
participant: Identity |
sd(_cons) | .8894606 .174943 .6049349 1.30781
-----------------------------+------------------------------------------------
sd(Residual) | .7382291 .0259892 .6890087 .7909655
------------------------------------------------------------------------------
LR test vs. linear regression: chibar2(01) = 174.61 Prob >= chibar2 = 0.0000
.
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment