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From |
Michael Housman <mhousman@evolvondemand.com> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
st: Testing for significant differences between groups after running a random-effects regression |

Date |
Tue, 9 Oct 2012 15:57:00 +0000 |

Hi folks, Was wondering if anyone could tell me how to test for significant differences between groups after running a random-effects regression? By way of background, I have data in which each observation represents an employee-date and the dependent variable is a performance metric (e.g., average handle time, customer satisfaction, etc.) for call center agents. In essence, I'm trying to model performance and plot the learning curve as a function of "day_of_service" for four different groups of employees. I've generated a variable called "hire_score_order" that's numbered 1 to 4, representing the four different groups that I want to represent. I've interacted that term twice with day_of_service so I can visually represent the first- and second-order effects. I've copied below my "xtreg" command and the resulting output for a sample metric. What I want to do is run xtreg post-estimation to test the hypothesis that group 1's learning curve is significantly different than groups 2's, group 2's vs. group 3's, etc. Any suggestions? Thanks in advance! Best, Mike xtreg aht c.day_of_service##c.day_of_service##i.hire_score_order, re Random-effects GLS regression Number of obs = 242792 Group variable: emp_id Number of groups = 1984 R-sq: within = 0.0049 Obs per group: min = 1 between = 0.1248 avg = 122.4 overall = 0.0622 max = 500 Wald chi2(38) = 1544.57 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 -------------------------------------------------------------------------------------------------------------------- aht | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---------------------------------------------------+---------------------------------------------------------------- day_of_service | -.0035472 .0302398 -0.12 0.907 -.0628162 .0557218 | c.day_of_service#c.day_of_service | -9.38e-07 4.63e-06 -0.20 0.839 -.00001 8.13e-06 | hire_score_order | 2 | 168.1932 48.20808 3.49 0.000 73.70711 262.6793 3 | 20.51885 68.23659 0.30 0.764 -113.2224 154.2601 4 | 156.1946 109.0574 1.43 0.152 -57.55392 369.9431 | hire_score_order#c.day_of_service | 2 | -2.088015 .5027992 -4.15 0.000 -3.073483 -1.102546 3 | -1.117207 .4928079 -2.27 0.023 -2.083092 -.1513208 4 | -2.408916 1.294864 -1.86 0.063 -4.946802 .1289699 hire_score_order#c.day_of_service#c.day_of_service | 2 | .0023866 .0016018 1.49 0.136 -.0007529 .0055262 3 | .0014925 .0014822 1.01 0.314 -.0014126 .0043976 4 | .0040321 .0037677 1.07 0.285 -.0033524 .0114167 | _cons | 246.4581 81.31057 3.03 0.002 87.09236 405.8239 ---------------------------------------------------+---------------------------------------------------------------- sigma_u | 521.47501 sigma_e | 930.20434 rho | .23912442 (fraction of variance due to u_i) -------------------------------------------------------------------------------------------------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Testing for significant differences between groups after running a random-effects regression***From:*Joerg Luedicke <joerg.luedicke@gmail.com>

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