NSF IIS CHS 2019

Main Exp: Error Analysis

	Estimate	Std..Error	t.value	p.z
(Intercept)	2.3073887	0.1863673	12.3808695	0.0000000
referance_frameLR	-0.0795455	0.1756698	-0.4528122	0.6506840
referance_frameUD	-0.4431818	0.1756698	-2.5228110	0.0116421
Condition.Out	0.6424185	0.2455826	2.6158953	0.0088994
referance_frameLR:Condition.Out	-1.2410927	0.2486149	-4.9920295	0.0000006
referance_frameUD:Condition.Out	-0.6988636	0.2484347	-2.8130680	0.0049071

Plot

Learning Time

#no Condition by SBSOD, TLX, Presence, Corsi, interactions

m.sem = lm(unity.time ~ Condition.*sbsod.mean + Condition.*raw.tlx + Condition.*presence + Condition.*Corsi.Span, data=full.long)

coefs <- data.frame(coef(summary(m.sem)))
# use normal distribution to approximate p-value
coefs$p.z <- 2 * (1 - pnorm(abs(coefs$t.value)))
knitr::kable(coefs, "html")%>%
  kable_styling(bootstrap_options = c("hover", "condensed", font_size = 12, full_width = F))

	Estimate	Std..Error	t.value	Pr…t..	p.z
(Intercept)	-569.49446	195.105402	-2.9189067	0.0035915	0.0035126
Condition.Out	2898.47662	264.386695	10.9630200	0.0000000	0.0000000
sbsod.mean	207.94101	19.676916	10.5677642	0.0000000	0.0000000
raw.tlx	64.88442	7.538097	8.6075331	0.0000000	0.0000000
presence	44.18244	16.318898	2.7074402	0.0068963	0.0067804
Corsi.Span	-14.48082	17.901243	-0.8089283	0.4187492	0.4185564
Condition.Out:sbsod.mean	-168.23732	23.207761	-7.2491835	0.0000000	0.0000000
Condition.Out:raw.tlx	-42.26915	10.470765	-4.0368734	0.0000583	0.0000542
Condition.Out:presence	-105.76975	20.703560	-5.1087711	0.0000004	0.0000003
Condition.Out:Corsi.Span	-311.14884	31.113909	-10.0003133	0.0000000	0.0000000

Plot

#summary stats for plot
time<- summarySE(full.long, "unity.time", groupvars="Condition.")


#plot (plot was made nicer in Illustrator)
timePlot <- time %>%
  ggplot(aes(x=Condition., y=unity.time)) +
    geom_bar(position=position_dodge(), stat="identity", color="#969494", fill="#afafaf") +
    geom_errorbar(aes(ymin=unity.time-ci, ymax=unity.time+ci),
                  width=.2,                    # Width of the error bars
                  position=position_dodge(.9)
                  )+
    labs(x = "Groups",
        y = "Time (ms)") +
    scale_x_discrete(labels = c("Inside Chart", "Outside Chart"))+
    theme_bw()
timePlot

Plot SBSOD + Time

#summary stats for plot

timeSBSOD<- summarySE(full.long, "unity.time", groupvars=c("Condition.", "sbsod.mean"))


#plot (plot was made nicer in Illustrator)
timeSBSODPlot <- timeSBSOD %>%
  ggplot(aes(x=sbsod.mean, y=unity.time, color=Condition., shape = Condition.)) +
  geom_point(size = 2.5) +
  stat_smooth(method = "lm",alpha=.1 )+
    labs(x = "Santa Barbara Sense of Direction Scale",
         y = "Time (ms)") +
    scale_color_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
  scale_shape_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
    theme_bw()
timeSBSODPlot

Plot Presence + Time

#summary stats for plot

timePresence<- summarySE(full.long, "unity.time", groupvars=c("Condition.", "presence"))


#plot (plot was made nicer in Illustrator)
  timePresence <- timePresence %>%
    ggplot(aes(x=presence, y=unity.time, color=Condition., shape = Condition.)) +
    geom_point(size = 2.5) +
    stat_smooth(method = "lm",alpha=.1 )+
      labs(x = "Presence",
           y = "Time (ms)") +
      scale_color_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
    scale_shape_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
      theme_bw()
  timePresence

Plot NASA TLX + Time

#summary stats for plot

timeTLX<- summarySE(full.long, "unity.time", groupvars=c("Condition.", "raw.tlx"))


#plot (plot was made nicer in Illustrator)
  timeTLXPlot <- timeTLX %>%
    ggplot(aes(x=raw.tlx, y=unity.time, color=Condition., shape = Condition.)) +
    geom_point(size = 2.5) +
    stat_smooth(method = "lm",alpha=.1 )+
      labs(x = "NASA TLX",
           y = "Time (ms)") +
      scale_color_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
    scale_shape_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
      theme_bw()
 timeTLXPlot

Plot Corsi + Time

Number of Error During Learning

#no Condition by SBSOD, TLX, Presence, Corsi, interactions

m.sem = lm(unity.num.errors ~ Condition.*sbsod.mean + Condition.*raw.tlx + Condition.*presence + Condition.*Corsi.Span, data=full.long)

coefs <- data.frame(coef(summary(m.sem)))
# use normal distribution to approximate p-value
coefs$p.z <- 2 * (1 - pnorm(abs(coefs$t.value)))
knitr::kable(coefs, "html")%>%
  kable_styling(bootstrap_options = c("hover", "condensed", font_size = 12, full_width = F))

	Estimate	Std..Error	t.value	Pr…t..	p.z
(Intercept)	-71.273999	30.174943	-2.3620260	0.0183666	0.0181754
Condition.Out	356.231494	40.889967	8.7119535	0.0000000	0.0000000
sbsod.mean	25.124259	3.043226	8.2557981	0.0000000	0.0000000
raw.tlx	2.754010	1.165840	2.3622542	0.0183553	0.0181642
presence	5.284074	2.523876	2.0936348	0.0365444	0.0362925
Corsi.Span	-2.394245	2.768601	-0.8647853	0.3873644	0.3871566
Condition.Out:sbsod.mean	-15.681701	3.589305	-4.3690070	0.0000138	0.0000125
Condition.Out:raw.tlx	1.954015	1.619405	1.2066253	0.2278624	0.2275765
Condition.Out:presence	-10.158541	3.202006	-3.1725547	0.0015572	0.0015110
Condition.Out:Corsi.Span	-44.020251	4.812068	-9.1478863	0.0000000	0.0000000

Plot Number of Errors

#summary stats for plot
time<- summarySE(full.long, "unity.num.errors", groupvars="Condition.")


#plot (plot was made nicer in Illustrator)
timePlot <- time %>%
  ggplot(aes(x=Condition., y=unity.num.errors)) +
    geom_bar(position=position_dodge(), stat="identity", color="#969494", fill="#afafaf") +
    geom_errorbar(aes(ymin=unity.num.errors-ci, ymax=unity.num.errors+ci),
                  width=.2,                    # Width of the error bars
                  position=position_dodge(.9)
                  )+
    labs(x = "Groups",
        y = "Number of Errors") +
    scale_x_discrete(labels = c("Inside Chart", "Outside Chart"))+
    theme_bw()
timePlot

Plot SBSOD + Number of Errors

Plot Presence + Number of Errors

#summary stats for plot

timePresence<- summarySE(full.long, "unity.num.errors", groupvars=c("Condition.", "presence"))


#plot (plot was made nicer in Illustrator)
  timePresence <- timePresence %>%
    ggplot(aes(x=presence, y=unity.num.errors, color=Condition., shape = Condition.)) +
    geom_point(size = 2.5) +
    stat_smooth(method = "lm",alpha=.1 )+
      labs(x = "Presence",
           y = "Number of Errors") +
      scale_color_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
    scale_shape_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
      theme_bw()
  timePresence

Plot NASA TLX + Number of Errors

#summary stats for plot

timeTLX<- summarySE(full.long, "unity.num.errors", groupvars=c("Condition.", "raw.tlx"))


#plot (plot was made nicer in Illustrator)
  timeTLXPlot <- timeTLX %>%
    ggplot(aes(x=raw.tlx, y=unity.num.errors, color=Condition., shape = Condition.)) +
    geom_point(size = 2.5) +
    stat_smooth(method = "lm",alpha=.1 )+
      labs(x = "NASA TLX",
           y = "Number of Errors") +
      scale_color_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
    scale_shape_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
      theme_bw()
 timeTLXPlot

Plot Corsi + Number of Errors

Number of Tries During Learning

#no Condition by SBSOD, TLX, Presence, Corsi, interactions

m.sem = lm(unity.num.tries ~ Condition.*sbsod.mean + Condition.*raw.tlx + Condition.*presence + Condition.*Corsi.Span, data=full.long)

coefs <- data.frame(coef(summary(m.sem)))
# use normal distribution to approximate p-value
coefs$p.z <- 2 * (1 - pnorm(abs(coefs$t.value)))
knitr::kable(coefs, "html")%>%
  kable_styling(bootstrap_options = c("hover", "condensed", font_size = 12, full_width = F))

	Estimate	Std..Error	t.value	Pr…t..	p.z
(Intercept)	-131.707728	52.814779	-2.4937665	0.0128005	0.0126396
Condition.Out	707.218117	71.569135	9.8816077	0.0000000	0.0000000
sbsod.mean	43.952326	5.326516	8.2516094	0.0000000	0.0000000
raw.tlx	7.957754	2.040553	3.8998028	0.0001027	0.0000963
presence	10.097794	4.417504	2.2858593	0.0224714	0.0222625
Corsi.Span	-1.171975	4.845843	-0.2418516	0.8089449	0.8088952
Condition.Out:sbsod.mean	-26.613574	6.282311	-4.2362714	0.0000248	0.0000227
Condition.Out:raw.tlx	-1.591787	2.834423	-0.5615912	0.5745207	0.5743946
Condition.Out:presence	-23.014034	5.604427	-4.1064027	0.0000435	0.0000402
Condition.Out:Corsi.Span	-85.435420	8.422495	-10.1437188	0.0000000	0.0000000

Plot Number of Tries

#summary stats for plot
time<- summarySE(full.long, "unity.num.tries", groupvars="Condition.")


#plot (plot was made nicer in Illustrator)
timePlot <- time %>%
  ggplot(aes(x=Condition., y=unity.num.tries)) +
    geom_bar(position=position_dodge(), stat="identity", color="#969494", fill="#afafaf") +
    geom_errorbar(aes(ymin=unity.num.tries-ci, ymax=unity.num.tries+ci),
                  width=.2,                    # Width of the error bars
                  position=position_dodge(.9)
                  )+
    labs(x = "Groups",
        y = "Number of Tries") +
    scale_x_discrete(labels = c("Inside Chart", "Outside Chart"))+
    theme_bw()
timePlot

Plot SBSOD + Number of Tries

Plot Presence + Number of Tries

#summary stats for plot

timePresence<- summarySE(full.long, "unity.num.tries", groupvars=c("Condition.", "presence"))


#plot (plot was made nicer in Illustrator)
  timePresence <- timePresence %>%
    ggplot(aes(x=presence, y=unity.num.tries, color=Condition., shape = Condition.)) +
    geom_point(size = 2.5) +
    stat_smooth(method = "lm",alpha=.1 )+
      labs(x = "Presence",
           y = "Number of Tries") +
      scale_color_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
    scale_shape_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
      theme_bw()
  timePresence

Plot NASA TLX + Number of Tries

#summary stats for plot

timeTLX<- summarySE(full.long, "unity.num.tries", groupvars=c("Condition.", "raw.tlx"))


#plot (plot was made nicer in Illustrator)
  timeTLXPlot <- timeTLX %>%
    ggplot(aes(x=raw.tlx, y=unity.num.tries, color=Condition., shape = Condition.)) +
    geom_point(size = 2.5) +
    stat_smooth(method = "lm",alpha=.1 )+
      labs(x = "NASA TLX",
           y = "Number of Tries") +
      scale_color_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
    scale_shape_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
      theme_bw()
 timeTLXPlot

Plot Corsi + Number of Tries

#summary stats for plot

timeCorsi<- summarySE(full.long, "unity.num.tries", groupvars=c("Condition.", "Corsi.Span"), na.rm=TRUE)


#plot (plot was made nicer in Illustrator)
  timeCorsiPlot <- full %>%
    ggplot(aes(x=Corsi.Span, y=unity.num.tries, color=Condition., shape = Condition.)) +
    geom_jitter(size = 2.5, width = 1) +
    stat_smooth(method = "lm",alpha=.1 )+
      labs(x = "Corsi.Span",
           y = "Number of Tries") +
      scale_color_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
    scale_shape_discrete(name = "Group", labels = c("Inside Chart", "Outside Chart"))+
      theme_bw()
 timeCorsiPlot

NSF IIS CHS 2019

Nov, 5th 2019

Main Exp: Error Analysis

Plot

Learning Time

Plot

Plot SBSOD + Time

Plot Presence + Time

Plot NASA TLX + Time

Plot Corsi + Time

Number of Error During Learning

Plot Number of Errors

Plot SBSOD + Number of Errors

Plot Presence + Number of Errors

Plot NASA TLX + Number of Errors

Plot Corsi + Number of Errors

Number of Tries During Learning

Plot Number of Tries

Plot SBSOD + Number of Tries

Plot Presence + Number of Tries

Plot NASA TLX + Number of Tries

Plot Corsi + Number of Tries