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. Author manuscript; available in PMC: 2017 Sep 1.
Published in final edited form as: Hisp Health Care Int. 2016 Jul 27;14(3):116–123. doi: 10.1177/1540415316660616

Table 3.

Hierarchical Linear Regression Analyses Demonstrating Main and Interactive Effects of Sociodemographic Variables and EDS on PHQ-9 Scores.

Predictor n b eb SE p
Model 1. Age and EDS
    Age 410 −.01 0.99 <.01 <.01
    EDS 410 .07 1.07 .01 <.01
    Age * EDS 410 <.01 1.00 <.01 .80
Model 2. Gender and EDS
    Gender 411 .12 1.12 .09 .20
    EDS 411 .07 1.07 .01 <.01
    Gender * EDS 411 <−.01 1.00 .02 .86
Model 3. Income and EDS
    Income 379 −.06 0.94 .02 <.01
    EDS 379 .07 1.07 .01 <.01
    Income * EDS 379 .01 1.01 .01 .32
Model 4. Acculturation and EDS
    Acculturation 399 .04 1.04 .04 .33
    EDS 399 .07 1.07 .01 <.01
    Acculturation * EDS 399 <.01 1.01 .01 .67
Model 5. Education and EDS
    Education 399 −.03 0.97 .02 .15
    EDS 399 .07 1.07 .01 <.01
    Education * EDS 399 .01 1.01 <.01 .08
Model 6. Health status and EDS
    Health status 409 −.28 0.76 .04 <.01
    EDS 409 .06 1.06 .01 <.01
    Health status * EDS 409 .02 1.02 .01 .06

Note. EDS = excessive daytime sleepiness; PHQ-9 = Patient Health Questionnaire-9; SE = standard error. Main effect statistics presented for each analysis are based on results of simultaneous linear regression models, as no interactions were statistically significant at α = .05.