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Table 3 Results of linear regression predicting alcohol consumption in high school a (n = 1,100).

From: High school drinking mediates the relationship between parental monitoring and college drinking: A longitudinal analysis

 

Bivariate Models

 

Multivariate Model c

 

b

SE

t ( df )

sr 2

p

 

b

SE

t ( df )

sr 2

p

Parental Monitoring Score

-.13

.01

-10.49 (1,194)

.08

<.0001

 

-.12

.01

-9.26 (1,092)

.07

<.0001

Sex [Reference = Female]

.97

.16

6.14 (1,249)

.03

<.0001

 

.69

.16

4.32 (1,092)

.01

<.0001

Race [Reference = Non-White]

1.37

.17

7.91 (1,246)

.05

<.0001

 

1.26

.18

7.02 (1,092)

.04

<.0001

Religiosityb [Reference = Slightly/Not Important]

-.56

.16

-3.46 (1,243)

.01

.0006

 

-.10

.16

-.59 (1,092)

<.01

.56

R 2

      

.14

F (df, df) p

      

24.82 (7, 1,092) p < .0001

  1. Effects were evaluated using the null hypothesis test of b = 0 (tested as: b/SE) which evaluates the unique contribution of a variable in a regression equation.
  2. a High school alcohol consumption was defined as the typical number of drinks per drinking day during the past year at the screener.
  3. b Religiosity was dichotomized into a binary variable (i.e., extremely/moderately vs. slightly/not).
  4. c As a proxy for socioeconomic status, the effect of mother's education was held constant in the multivariate model. Effect size (sr2) for each explanatory variable was as follows: parental monitoring score (.07), sex (.01), race (.04), religiosity (<.01), mother's education (<.01).