Intro:

This is the document to house the stats for EMO3 & EMO4 study - used for invited publication in Brain Sciences, Open Access

EMO3 is a comparison of younger adults with a simulated hearing loss. We compared these individuals with yougner adults with normal hearing (no simulation) and younger adults with normal hearing who heard stimuli that were processed, but without attenuation (i.e., without the simulated HL). This resulted in a control for the other factors of the processing.

Emo4 is our older adult control group - using a sample of older adult with (essentially) normal hearing (loss at/after 4k was allowed in order to get a sample)

Sanity check

First, we confirm that the EMO3 processed stimuli without simulation are similar to the YNH (ie no effect of listener group between these two groups - no effect of processing unrelated to the HL)

Here's our model comparing LG, TG, and Style for YNH and unprocessed stimuli

YprocData <- subset(dat, LG == 0 | LG==1)
ProcModel <- lmer(Anger ~ Style*LG*TG + (1|TalkerNo), data = YprocData)
anova(ProcModel)

These results show a significant effect if speaking style on perceived anger (expected) and a significant interaction between speaking style and talker group (more vs less clear speakers) but no listener group effect, or any interactions involving listener group (suggesting no effect of processing).

Experiment I (EMO3):

The next step is to evaluate the comparison of simulated HL vs younger adults wtih normal hearing (for a hearing loss comparison) and simulated hearing loss vs older adults with hearing loss (for an aging comparison).

#test  YNH simHL vs OHL
YSimData <- subset(dat, LG == 0 | LG==2 | LG == 4)
YSimModel <- lmer(Anger ~ Style*LG*TG + (1|TalkerNo), data = YSimData)
anova(YSimModel)

Results show a significant effect of style, style x talker group, and 3-way interaction (style x TG is smaller for OHL than for YNH and YSIM). The 3-way indicates that the OHL anger is significantly less than both the simHL and YNH ratings of anger.

Experiment II (EMO4):

Next, we need to compare ONH data from EMO4 with YNH and OHL data from Morgan and Ferguson (2017). The model used to assess this is below -

#test  YNH ONH vs OHL
ONHdata <- subset(dat, LG == 0 | LG==3 | LG == 4)
ONHmodel <- lmer(Anger ~ Style*LG*TG + (1|TalkerNo), data = ONHdata)
anova(ONHmodel)

Same deal here - results showing a significant style effect, significant style x talker group interaction, but a 3-way talker group x listener group x style interaction - suggesting more anger selection by YNH than ONH and OHL listeners.

Confirming group differences

Morgan and Ferguson (2017) showed sig. differences between YNH and OHL - so if YSIM is more like YNH and ONH is more like OHL, then we should see differences between YSIM and ONH that are similar to Morgan & Ferguson (2017).

Final analysis to confirm all of this is the comparison of YSim and ONH - showing a significant listener group difference, style x talker group interaction and 3-way (that the style x talker group magnitude differs by LG)

Statistical model to confirm:

#test  YNH ONH vs OHL
ONHvYsimData <- subset(dat, LG == 2 | LG==3)
ONHvYsimModel <- lmer(Anger ~ Style*LG*TG + (1|TalkerNo), data = ONHvYsimData)
anova(ONHvYsimModel)

Plots, because R is beautiful