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Table 2 Hierarchical Multiple Linear Regression Analyses of Purpose in Life and Sleep Quality

From: Is purpose in life associated with less sleep disturbance in older adults?

  

B

SE

β

p

F

R 2

Sleep Quality at Baseline (n = 814)

Step 1

    

2.41 (4) *

.012

 Sex

−.324

.234

−.049

.167

  

 Years of Education

−.016

.032

−.018

.618

  

 Age

.004

.014

.012

.755

  

Race

.534

.210

.095

.011

  

Step 2

9.383 (5) **

.055

 Sex

−.298

.229

−.045

.193

  

 Years of Education

.023

.032

.026

.471

  

 Age

−.016

.014

−.042

.261

  

Race

.548

.206

.097

.008

  

Purpose in Life

−1.326

.218

−.220

.000

  

Sleep Quality Change Baseline to

1-Year Follow-up (n = 814)

Step 1

    

.556(4)

.003

 Sex

−.119

.202

−.021

.555

  

 Education

−.029

.028

−.037

.293

  

 Age

−.011

.012

−.034

.367

  

 Race

−.074

.181

−.407

.684

  

Step 2

    

1.546 (5)

.009

 Sex

−.128

2.01

−.022

.526

  

 Years of Education

−.043

.028

−.055

.132

  

 Age

−.004

.012

−.012

.746

  

 Race

−.078

.180

−.016

.665

  

Purpose in Life

.449

.192

.087

.019

  

Sleep Quality Change Baseline to

2-Year Follow-up (n = 550)

Step 1

    

.857(4)

.006

 Sex

.098

.245

.017

.689

  

 Education

−.032

.034

−.040

.352

  

 Age

.018

.016

.050

.269

  

 Race

.265

.226

.053

.240

  

Step 2

    

.855 (5)

.008

 Sex

.087

.245

.015

.724

  

 Years of Education

−.039

.035

−.049

.270

  

 Age

.021

.016

.058

.205

  

 Race

.261

.226

.052

.249

  

 Purpose in Life

.235

.255

.041

.357

  

Sleep Quality Change Baseline to

3-Year Follow-up (n = 245)

Step 1

    

.593(4)

.012

 Sex

−.398

.357

−.072

.266

  

 Education

.014

.054

.016

.801

  

 Age

.007

.025

.018

.787

  

 Race

.412

.345

.081

.234

  

Step 2

    

.693 (5)

.013

 Sex

−.388

.358

−.071

.279

  

 Years of Education

.022

.057

.026

.702

  

 Age

.003

.026

.008

.914

  

 Race

.396

.347

.078

.255

  

 Purpose in Life

−.183

.363

−.036

.615

  
  1. Four separate regression analyses. * = p ≤ .05, ** = p ≤ .01, bolding is used to emphasize significant predictors within the models