. Author manuscript; available in PMC: 2016 Mar 1.

Published in final edited form as: J Diabetes Complications. 2014 Nov 13;29(2):250–257. doi: 10.1016/j.jdiacomp.2014.11.003

Table 3.

Multiple Regression Analyses.

	Unstandardized Coefficients		Standardized Coefficients
	β	Std. Error	β	t	Sig.	β 95% CI
Constant	34.977	2.098		16.68	<.001	(30.706, 39.289)
T2DMPN	−3.468	1.318	−.446	−2.632	.01	(−6.163, −.773)
T2DM	−2.132	1.439	−.252	−1.481	.14	(−5.074, .811)
%IMAT	−.096	.030	−.461	−3.159	.004	(−.158, −.034)
Normalized PF Power 60 deg/sec	8.876	9.917	.127	.895	.37	(−11.406, 29.158)
Model Sig.: F = 7.121, df=4, p<.001 Nagelkerke R²=.496 Unique Variance (PPT) accounted for: %IMAT= 17.4%, T2DMPN status= 12%, PF Power= 1.4%, T2DM status= 3.8%

Linear regression model to determine 9-item PPT score from PF power, muscle quality and composition (%IMAT), and disease status. Beta coefficients for each predictor represent change in PPT score due to disease status or 1 unit change in %IMAT or PF power. Model significance, amount of variance in 9-item PPT score explained by the model (R²), and amount of variance in PPT explained by each predictor are shown in the bottom panel.