File: Exp1_BehaviouralAnalyses_Code.R

Comment:  construct a maximal glmer() model  This model contains a fixed withinsubjects effect of Ambiguity (effectcoded with 0.5 amb),  codes for modality effects and interactions,  plus random effects by participants and items. 
Category: Statistical Modeling
Code:
Acc.max <- glmer(Correct ~ 1 + Ambiguity.code + Modality.code1 + Modality.code2 + Interaction.code1 + Interaction.code2 + (1 + Ambiguity.code + Modality.code1 + Modality.code2 + Interaction.code1 + Interaction.code2 | Participant.Private.ID) + (1   | Item), data = Data.CohOnly, family = "binomial", control = glmerControl(optimizer ="bobyqa")) Acc.max <- glmer(Correct ~ 1 + Ambiguity.code + Modality.code2 + Interaction.code2 + (1 + Ambiguity.code + Modality.code2 + Interaction.code2 | Participant.Private.ID) + (1   | Item), data = Data.ListandRead, family = "binomial", control = glmerControl(optimizer ="bobyqa")) Acc.max <- glmer(Correct ~ 1 + Ambiguity.code + Modality.code3 + Interaction.code3 + (1 + Ambiguity.code + Modality.code3 + Interaction.code3 | Participant.Private.ID) + (1   | Item), data = Data.ListandRSVP, family = "binomial", control = glmerControl(optimizer ="bobyqa"))

Comment:  construct a maximal lmer() model  This model contains codes for modality effects,  plus random effects by participants and items. 
Category: Statistical Modeling
Code:
RT.AmbOnly.max <- lmer(logRT ~ 1 + Modality.code1 + Modality.code2 + (1 + Modality.code1 + Modality.code2 | Participant.Private.ID) + (1   | Item), data = Data.AmbOnly, REML=FALSE) RT.ListandRead.max <- lmer(logRT ~ 1 + Modality.code2 + (1 + Modality.code2 | Participant.Private.ID) + (1   | Item), data = Data.ListandRead, REML=FALSE) RT.ListandRSVP.max <- lmer(logRT ~ 1 + Modality.code3 + (1 + Modality.code3 | Participant.Private.ID) + (1   | Item), data = Data.ListandRSVP, REML=FALSE) RT.ReadandRSVP.max <- lmer(logRT ~ 1 + Modality.code3 + (1 + Modality.code3 | Participant.Private.ID) + (1   | Item), data = Data.ReadandRSVP, REML=FALSE) RT.UAOnly.max <- lmer(logRT ~ 1 + Modality.code1 + Modality.code2 + (1 + Modality.code1 + Modality.code2 | Participant.Private.ID) + (1   | Item), data = Data.UAOnly, REML=FALSE) RT.ListandRead.max <- lmer(logRT ~ 1 + Modality.code2 + (1 + Modality.code2 | Participant.Private.ID) + (1   | Item), data = Data.ListandRead, REML=FALSE) RT.ListandRSVP.max <- lmer(logRT ~ 1 + Modality.code3 + (1 + Modality.code3 | Participant.Private.ID) + (1   | Item), data = Data.ListandRSVP, REML=FALSE) RT.ReadandRSVP.max <- lmer(logRT ~ 1 + Modality.code3 + (1 + Modality.code3 | Participant.Private.ID) + (1   | Item), data = Data.ReadandRSVP, REML=FALSE)

Comment:  construct a maximal lmer() model  This model contains a fixed effect for Ambiguity,  plus random effects by participants and items. 
Category: Statistical Modeling
Code:
RT.ListeningOnly.max <- lmer(logRT ~ 1 + Ambiguity.code + (1 + Ambiguity.code | Participant.Private.ID) + (1   | Item), data = Data.ListeningOnly, REML=FALSE) RT.ReadingOnly.max <- lmer(logRT ~ 1 + Ambiguity.code + (1 + Ambiguity.code | Participant.Private.ID) + (1   | Item), data = Data.ReadingOnly, REML=FALSE) RT.RSVPOnly.max <- lmer(logRT ~ 1 + Ambiguity.code + (1 + Ambiguity.code | Participant.Private.ID) + (1   | Item), data = Data.RSVPOnly, REML=FALSE)