Embedded Implicature

Preliminaries.

rm(list=ls())
setwd("~/Projects/R/embed_ball")
source("~/Projects/R/Ranalysis/useful.R")

## Loading required package: Matrix
## Loading required package: Rcpp

Read in data.

d <- read.csv("data/basketball-pilot-2-11-14-results-parsed.csv")
tt <- read.csv("data/trial_types.csv")

Filter out the training trials.

d <- subset(d,is.na(trainingCorrect))
d$condition <- factor(d$condition)

Annoying releveling of factors so that everything looks nice on plots.

d$quant1 <- NA
d$quant1[grepl("Every",d$sentence)] <- "Every"
d$quant1[grepl("Exactly one",d$sentence)] <- "Exactly one"
d$quant1[grepl("No",d$sentence)] <- "No"
d$quant1 <- factor(d$quant1,levels=c("No","Exactly one","Every"))

d$quant2 <- NA
d$quant2[grepl("none",d$sentence)] <- "None"
d$quant2[grepl("some",d$sentence)] <- "Some"
d$quant2[grepl("all",d$sentence)] <- "All"
d$quant2 <- factor(d$quant2,levels=c("None","Some","All"))

d$condition <- revalue(d$condition,
                       c("none-none-none"="NNN",
                         "none-none-half"="NNS",
                         "none-none-all"="NNA",
                         "none-half-half"="NSS",
                         "none-half-all"="NSA",                         
                         "none-all-all"="NAA",
                         "half-half-half"="SSS",
                         "half-half-all"="SSA",
                         "half-all-all"="SAA",
                         "all-all-all"="AAA"))  
d$condition <- factor(d$condition, levels=c("NNN",
                                      "NNS",
                                      "NNA",
                                      "NSS",
                                      "NSA",
                                      "NAA",
                                      "SSS",
                                      "SSA",
                                      "SAA",
                                      "AAA"))          

Merge in independent truth value judgments on each sentence (from Chris and Dan). Not a necessary step, but useful for coloring graph.

dtt <- merge(d,tt)
dtt$truth <- dtt$truth.chris==1 & dtt$truth.dan==1

Analysis

Aggregate data, first within and then across participants.

mss <- aggregate(response ~ condition + sentence + trial.type + quant1 + quant2 + truth + workerid, 
                 data=dtt, mean)
ms <- aggregate(response ~ condition + sentence + trial.type + quant1 + quant2 + truth, 
                data=mss, mean)
ms$cih <- aggregate(response ~ condition + sentence + trial.type + quant1 + quant2 + truth, data=mss, ci.high)$response
ms$cil <- aggregate(response ~ condition + sentence + trial.type + quant1 + quant2 + truth, data=mss, ci.low)$response
ms$n <- aggregate(workerid ~ condition + sentence + trial.type + quant1 + quant2 + truth, data=mss, n.unique)$workerid

Now plot

ggplot(subset(ms,trial.type=="target"),
       aes(x=condition, y=response, fill=truth, ymin=response-cil,
           ymax=response+cih)) + 
  geom_bar(stat="identity") + 
  geom_linerange() +
  scale_y_continuous(breaks=c(1,3,5,7)) + 
  facet_grid(quant1~quant2) + 
  geom_text(aes(x=5.5,y=7,label=sentence),hjust=.5,cex=3) +
  theme(axis.text.x = element_text(angle = 90,vjust=0.5))

Histogram of likert scale usage for key condition, C&S Experiment 2. “Exactly one player hit some of his shots.”

qplot(response,facets=.~condition, binwidth=1,
      data=subset(mss,trial.type=="target" &
                  sentence=="Exactly one player hit some of his shots")) + 
  scale_x_continuous(breaks=c(1,3,5,7))

And for “no … none”:

qplot(response,facets=.~condition,binwidth=1,
      data=subset(mss,trial.type=="target" &
                    sentence=="No player hit none of his shots"))

And for “Every … some” (C&S Experiment 1):

qplot(response,facets=.~condition,binwidth=1,
      data=subset(mss,trial.type=="target" &
                    sentence=="Every player hit some of his shots"))

Now for the key “some” column of the larger plot.

qplot(response,facets=quant1~condition,binwidth=1,
      data=subset(mss,trial.type=="target" &
                    quant2=="Some"))