Table 3.

Linear regresssion and commonality analysis for SRTHP

lm=β1X1+β2X2+ϵ Adj. R2 F (df1,df2)pparametersuniquecommon
SRTSiN-HP0.60F(2, 41) = 33.01<.05β1 = −13.11**14.1%61.2%
X1 = RAM EFRβ2 = 0.1***24.7%
X2 = THA,4 kHz ϵ = 2.87*
SRTSiN-HP,NH0.64F(2, 27) = 26.86<.05β1 = −13.20***34.7%24.3%
β2 = 0.22***41.0%
ϵ = 2.09*
SRTSiN-HP,OLD0.23F(2, 26) = 5.3=0.01β1 = −5.094.2%42.3%
β2 = 0.07*53.5%
ϵ = 2.90*
SRTSiQ-HP0.75F(2, 41) = 66.95<.05β1 = −10.260.5%44.8%
β2 = 0.6***54.7%
ϵ = 37.78***
SRTSiQ-HP,NH0.61F(2, 27) = 24.64<.05β1 = −10.72.2%12.71%
β2 = 1.02***85.0%
ϵ = 35.0***
SRTSiQ-HP,OLD0.6F(2, 26) = 22.2<.01β1 = 17.161.4%15.6%
β2 = 0.53***83%
ϵ = 37.14***
  • Linear regression models for SRTHP in noise (SiN) or in quiet (SiQ). Regressions were performed on the entire cohort as well as in subgroups of normal-hearing (NH), or older (OLD) subjects. All models had a normal distribution of residuals, and a colinearity (vif) factor below 1.61 (i.e., independent parameters). Significance codes: ***p ≤ .001, **p ≤ .01, *p ≤ .05.