Table 5

Sequential comparison of multinomial logistic models for the prediction of physical activity frequency in girls (n = 3 119)

Statistics for individual predictors

Model statistics


Model

Age

Pubic hair stage

Menarche

Pubertal timing

BDS

Region × body fat

SES × body fat

Correct classification

Pseudo -2 Log-Likelihood

Wald χ2 (df) corr. for model

Nagelkerke's pseudo R2


0#

Wald χ2 (df) corrected

36.2%

9393.16

92.77 (12.99)

.045

p-value*‚

< .001


1

Wald χ2 (df) corrected

112.22 (2.90)

36.7%

9222.36

178.55 (15.38)

.093

p-value *

< .001

< .001


2

Wald χ2 (df) corrected

41.32

(2.80)

6.23

(5.74)

8.71 (5.60)

37.5%

9201.17

181.48 (24.41)

.099

p-value*

< .001

.506

.152

< .001


3

Wald χ2 (df) corrected

40.28 (2.88)

5.98 (5.75)

6.94 (5.61)

16.70 (5.72)

38.1%

9177.39

185.18 (27.99)

.106

p-value*

< .001

.588

.177

.480

< .001


4

Wald χ2 (df) corrected

39.54 (2.90)

5.65 (5.76)

7.85 (5.61)

17.12 (5.71)

21.38

(8.45)

38.2%

9146.57

189.62 (33.27)

.114

p-value*

< .001

.635

.135

.414

.014

< .001


5

Wald χ2 (df) corrected

38.57 (2.90)

5.79 (5.75)

7.70 (5.60)

17.07 (5.70)

21.40 (8.43)

5.75 (2.92)

8.24 (5.68)

38.1%

9128.14

194.32 (38.08)

.119

p-value*

< .001

.616

.147

.372

.012

.048

.017

< .001


* Adjustment for multiple tests: Šidák sequential

# model 0 = baseline model including body fat percentage and sociodemographic variables: region, SES, migrant background

Each row of the table shows the results of one tested model. Left-hand the test statistics for the independent variables are given while right-hand information on model fit is displayed.

The corrected Wald chi-square test tests if an individual independent variable (individual predictors) or all independent variables together (model statistics) significantly contribute to the prediction of the dependent variable; it is corrected for the sampling plan.

Correct classification rate is the proportion of participants for whom the tested model could correctly predict the category of the dependent variable (PA frequency).

Pseudo -2 Log-Likelihood: In logistic regression models are compared due to their -2 log-likelihood; since for complex samples no likelihood ratio test is available the values are only descriptive; better fitting models have smaller values.

Nagelkerke's pseudo R2 is a measure of explained variation in the dependent variable that emulates R2 from linear regression.

Finne et al. International Journal of Behavioral Nutrition and Physical Activity 2011 8:119   doi:10.1186/1479-5868-8-119

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