Syntactic Bootstrapping Publication Bias
Anjie Cao and Molly Lewis
8/24/2020
DATA_PATH <- here("data/processed/syntactic_bootstrapping_tidy_data.csv")
ma_data <- read.csv(DATA_PATH) %>% mutate(row_id = 1:n())Forest Plot
There are 60 effect sizes from 18 unique papers.
get_MA_params <- function(moderator, df) {
this_data <- df
n = nrow(this_data)
if (moderator == TRUE){
model <- rma.mv(d_calc ~ log(mean_age), V = d_var_calc,
random = ~ 1 | short_cite/same_infant/x_1,
method = "REML",
data = this_data)
this_moderator_estimate <- model$b[2]
this_moderator_estimate.cil <- model$ci.lb[2]
this_moderator_estimate.cih <- model$ci.ub[2]
this_moderator_z <- model$zval[2]
this_moderator_p <- model$pval[2]
} else{
model <- rma.mv(d_calc, V = d_var_calc,
random = ~ 1 | short_cite/same_infant/x_1,
method = "REML",
data = this_data)
this_moderator_estimate <- NA
this_moderator_estimate.cil <- NA
this_moderator_estimate.cih <- NA
this_moderator_z <- NA
this_moderator_p <- NA
}
params <- data.frame(this_moderator = moderator,
n = n,
estimate = model$b[1],
estimate.cil = model$ci.lb[1],
estimate.cih = model$ci.ub[1],
z = model$zval[1],
p = model$pval[1],
mod_estimate = this_moderator_estimate,
mod_estimate.cil = this_moderator_estimate.cil,
mod_estimate.cih = this_moderator_estimate.cih,
moderator_z = this_moderator_z,
moderator_p = this_moderator_p,
Q = model$QE,
Qp = model$QEp)
}
null_model<- get_MA_params(FALSE, ma_data)
#null_model
age_model <- get_MA_params(TRUE, ma_data)
all_models <- bind_rows(null_model,age_model)
mod_print <- all_models %>%
mutate(esimate_print = round(estimate, 2),
CI_print = paste0(" [",
round(estimate.cil, 2),
", ",
round(estimate.cih, 2),
"]"),
estimate_print_full = paste(esimate_print, CI_print),
z_print = round(z, 2),
p_print = round(p, 2),
p_print = ifelse(p_print <.001, "<.001", paste0("= ", p_print)),
mod_estimate_print = round(mod_estimate, 2),
mod_CI_print = paste0(" [",
round(mod_estimate.cil, 2),
", ",
round(mod_estimate.cih, 2),
"]"),
mod_estimate_print_full = paste(mod_estimate_print, mod_CI_print),
mod_z_print = round(moderator_z, 2),
mod_p_print = round(moderator_p, 2),
mod_p_print = ifelse(mod_p_print < .001, "<.001",
paste0("= ", mod_p_print)),
Q_print = round(Q, 2),
Qp_print = round(Qp, 2),
Qp_print = ifelse(Qp_print < .001, "<.001", paste0("= ", Qp_print)))alpha = 0.05
individual_data <- ma_data %>%
select(short_cite, unique_id,d_calc,d_var_calc, n_1, plot_label,sentence_structure) %>%
mutate(cil = d_calc - (qnorm(alpha / 2, lower.tail = FALSE) * sqrt(d_var_calc)),
cil = case_when(
(cil < -8) ~ -8, # truncate error bar for visibility reason
TRUE ~ cil
),
ciu = d_calc +
qnorm(alpha / 2, lower.tail = FALSE) * sqrt(d_var_calc),
meta = "no",
label_color = "black",
print_full = paste(round(d_calc,2), " [",round(cil,2),", ",round(ciu,2), "]", sep = "")
)
cumulative <- mod_print %>%
filter(this_moderator == FALSE) %>%
select (estimate, estimate.cil, estimate.cih) %>%
mutate(short_cite = "Meta-Analytic Effect Size",
plot_label = "Meta-Analytic Effect Size",
d_calc = estimate,
d_var_calc = NA,
n_1 = 99,
expt_num = "",
expt_condition = "",
cil = estimate.cil,
ciu = estimate.cih,
sentence_structure = "cumulative",
print_full = paste(round(d_calc,2), " [",round(cil,2),", ",round(ciu,2), "]", sep = ""),
meta = "yes",
label_color = "red")
forest_data <- bind_rows(individual_data, cumulative)
forest_data$sentence_structure <- as.factor(forest_data$sentence_structure)
forest_data$meta <- as.factor(forest_data$meta)
forest_data <- forest_data %>%
rowid_to_column() %>%
mutate(
rowid = if_else(rowid == 0, 99, as.double(rowid)) #to always put the MA ES at bottom
) %>%
group_by(sentence_structure) %>% arrange(-rowid, .by_group = TRUE)
forest_data$plot_label <- factor(forest_data$plot_label, levels = forest_data$plot_label)
# set the neighbourhood levels in the order the occur in the data frame
label_colors <- forest_data$label_color[order(forest_data$plot_label)]
forest_data %>% # First sort by val. This sort the dataframe but NOT the factor levels
ggplot(aes(x = plot_label, y = d_calc)) +
geom_point(data = forest_data,
aes(size=n_1, shape = sentence_structure, color = sentence_structure)) +
scale_color_manual(breaks = c("cumulative", "intransitive","transitive"),
values = c("red", "black", "black"))+
scale_size(guide = 'none') +
scale_shape_manual(breaks = c("cumulative", "intransitive","transitive"),
values=c(18,16, 17)) +
#guides(color = guide_legend(override.aes = list(shape = 18, shape = 16, shape = 17))) +
geom_linerange(aes(ymin = cil, ymax = ciu, color = sentence_structure), show.legend = FALSE) +
geom_segment(aes(x = plot_label, y = d_calc, xend = plot_label, yend = cil),
linejoin = "round",
lineend = "round",
size = 0.1,
arrow = arrow(length = unit(0.1, "inches")),
data = filter(forest_data,cil == -8))+
geom_hline(aes(yintercept = 0), color = "gray44",linetype = 2) +
geom_hline(aes(yintercept = filter(forest_data, sentence_structure == "cumulative")$d_calc),
color = "red", linetype = 2) +
geom_text(aes(label = print_full, x = plot_label, y = 7),
size = 3.5, colour = label_colors) +
scale_y_continuous(breaks = seq(-10, 5, 1))+
coord_cartesian(clip = 'on') +
coord_flip() +
ylab("Cohen's d") +
labs(color = "Effect Size Type",shape = "Effect Size Type") + # merge two legends
theme(text = element_text(size=18),
legend.position="bottom",
plot.margin = unit(c(1,2,16,1), "lines"),
legend.title = element_blank(),
panel.background = element_blank(),
#panel.background = element_rect(fill = "white", colour = "grey50"),
axis.title.y = element_blank(),
axis.text.y = element_text(colour = label_colors)) 
Funnel Plot with Base Model
base_model_mv <- rma.mv(d_calc, d_var_calc,
random = ~ 1 | short_cite/same_infant/row_id, data=ma_data)
funnel(base_model_mv)
Regression Test
Base Model Regression Test
Base model suggests the funnel plot is asymmetrical
base_model_no_mv <- rma(d_calc, d_var_calc, data=ma_data)
regtest(base_model_no_mv, predictor = 'sei', ret.fit = T)##
## Regression Test for Funnel Plot Asymmetry
##
## model: mixed-effects meta-regression model
## predictor: standard error
##
## Mixed-Effects Model (k = 60; tau^2 estimator: REML)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1735 (SE = 0.0494)
## tau (square root of estimated tau^2 value): 0.4165
## I^2 (residual heterogeneity / unaccounted variability): 67.90%
## H^2 (unaccounted variability / sampling variability): 3.12
## R^2 (amount of heterogeneity accounted for): 19.82%
##
## Test for Residual Heterogeneity:
## QE(df = 58) = 176.2327, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 15.7334, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.6975 0.2526 -2.7606 0.0058 -1.1926 -0.2023 **
## sei 3.2098 0.8092 3.9665 <.0001 1.6238 4.7959 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## test for funnel plot asymmetry: z = 3.9665, p < .0001Multi-level Model Regression Test
Similar pattern using multi-level model, also significantly asymmetrical.
rma.mv(d_calc ~ sqrt(d_var_calc), d_var_calc,
random = ~ 1 | short_cite/same_infant/row_id, data=ma_data)##
## Multivariate Meta-Analysis Model (k = 60; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 0.1502 0.3875 18 no short_cite
## sigma^2.2 0.0501 0.2238 59 no short_cite/same_infant
## sigma^2.3 0.0000 0.0000 60 no short_cite/same_infant/row_id
##
## Test for Residual Heterogeneity:
## QE(df = 58) = 176.2327, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 20.4756, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.9665 0.2886 -3.3485 0.0008 -1.5323 -0.4008 ***
## sqrt(d_var_calc) 4.3507 0.9615 4.5250 <.0001 2.4662 6.2352 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Multi-level Model with Moderators Regression Test
When including theoretically relevant moderators, it is still shows significant asymmetry.
rma.mv(d_calc ~ sqrt(d_var_calc) + mean_age + agent_argument_type +
test_mass_or_distributed + test_method + n_repetitions_video, random = ~ 1 | short_cite/same_infant/row_id, d_var_calc, data = ma_data)##
## Multivariate Meta-Analysis Model (k = 60; method: REML)
##
## Variance Components:
##
## estim sqrt nlvls fixed factor
## sigma^2.1 0.1357 0.3683 18 no short_cite
## sigma^2.2 0.0528 0.2297 59 no short_cite/same_infant
## sigma^2.3 0.0000 0.0000 60 no short_cite/same_infant/row_id
##
## Test for Residual Heterogeneity:
## QE(df = 53) = 140.1155, p-val < .0001
##
## Test of Moderators (coefficients 2:7):
## QM(df = 6) = 26.2445, p-val = 0.0002
##
## Model Results:
##
## estimate se zval pval ci.lb
## intrcpt -1.5596 0.5504 -2.8337 0.0046 -2.6384
## sqrt(d_var_calc) 4.8097 1.1196 4.2960 <.0001 2.6154
## mean_age 0.0000 0.0003 0.1099 0.9125 -0.0005
## agent_argument_typepronoun -0.1273 0.2880 -0.4422 0.6584 -0.6918
## test_mass_or_distributedmass 0.1623 0.3561 0.4558 0.6486 -0.5357
## test_methodpoint 0.7713 0.5123 1.5057 0.1322 -0.2327
## n_repetitions_video 0.1183 0.0633 1.8673 0.0619 -0.0059
## ci.ub
## intrcpt -0.4809 **
## sqrt(d_var_calc) 7.0041 ***
## mean_age 0.0006
## agent_argument_typepronoun 0.4371
## test_mass_or_distributedmass 0.8603
## test_methodpoint 1.7753
## n_repetitions_video 0.2424 .
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1PublicationBias Package
P-val Plot
Publication bias favors “significant” results regardless of the sign.
pval_plot(ma_data$d_calc,
ma_data$d_var_calc, alpha.select = 0.05) 
Eta analysis
eta curve
When affirmative studies were 15 times more likely to be published than the non-affirmative studies, the estimate of the meta-analytic effect size is 0.
eta <- data.frame()
for (i in 1:20){
df <- corrected_meta(
ma_data$d_calc,
ma_data$d_var_calc,
eta= i,
clustervar = 1:length(ma_data$d_calc),
model = "robust",
selection.tails = 1, # if changed to 2, the curve is flat
favor.positive = TRUE,# if changed to False, the curve is flat
alpha.select = 0.05,
CI.level = 0.95,
small = TRUE)
eta <- bind_rows(eta, df)
}
eta## est se lo hi pval eta k.affirmative
## 1 0.27479422 0.07240619 0.129623069 0.4199654 0.0003755973 1 17
## 2 0.17926930 0.06707060 0.044231409 0.3143072 0.0103982981 2 17
## 3 0.14091726 0.06593967 0.007898524 0.2739360 0.0383807095 3 17
## 4 0.12023239 0.06576835 -0.012548524 0.2530133 0.0747400106 4 17
## 5 0.10729232 0.06585281 -0.025712554 0.2402972 0.1109388452 5 17
## 6 0.09843325 0.06600459 -0.034908244 0.2317748 0.1436148461 6 17
## 7 0.09198757 0.06616588 -0.041698267 0.2256734 0.1720648613 7 17
## 8 0.08708731 0.06631826 -0.046918561 0.2210932 0.1965579540 8 17
## 9 0.08323618 0.06645652 -0.051057498 0.2175299 0.2176301594 9 17
## 10 0.08012983 0.06658015 -0.054419727 0.2146794 0.2358304306 10 17
## 11 0.07757126 0.06669021 -0.057205216 0.2123477 0.2516420643 11 17
## 12 0.07542731 0.06678823 -0.059550683 0.2104053 0.2654678622 12 17
## 13 0.07360476 0.06687574 -0.061552784 0.2087623 0.2776364882 13 17
## 14 0.07203637 0.06695416 -0.063281789 0.2073545 0.2884143240 14 17
## 15 0.07067244 0.06702471 -0.064790016 0.2061349 0.2980173277 15 17
## 16 0.06947544 0.06708843 -0.066117218 0.2050681 0.3066212349 16 17
## 17 0.06841648 0.06714623 -0.067294144 0.2041271 0.3143698360 17 17
## 18 0.06747300 0.06719884 -0.068344951 0.2032910 0.3213815247 18 17
## 19 0.06662708 0.06724692 -0.069288882 0.2025430 0.3277544278 19 17
## 20 0.06586433 0.06729101 -0.070141454 0.2018701 0.3335704128 20 17
## k.nonaffirmative signs.recoded
## 1 43 FALSE
## 2 43 FALSE
## 3 43 FALSE
## 4 43 FALSE
## 5 43 FALSE
## 6 43 FALSE
## 7 43 FALSE
## 8 43 FALSE
## 9 43 FALSE
## 10 43 FALSE
## 11 43 FALSE
## 12 43 FALSE
## 13 43 FALSE
## 14 43 FALSE
## 15 43 FALSE
## 16 43 FALSE
## 17 43 FALSE
## 18 43 FALSE
## 19 43 FALSE
## 20 43 FALSEeta %>% ggplot(aes(x = eta, y = pval)) +
geom_point() +
geom_line() +
geom_hline(yintercept = 0.05, color = "red", type = 2) +
labs(title = "eta vs pval")
plot
eta.list = as.list( c( 200, 150, 100, 50, 40, 30, 20, rev( seq(1,15,1) ) ) )
res.list = lapply(eta.list, function(x){
cat("\n Working on eta = ", x)
return(corrected_meta(
ma_data$d_calc,
ma_data$d_var_calc,
eta= x,
clustervar = 1:length(ma_data$d_calc),
model = "robust",
selection.tails = 1,
favor.positive = TRUE,
alpha.select = 0.05,
CI.level = 0.95,
small = TRUE) )
})##
## Working on eta = 200
## Working on eta = 150
## Working on eta = 100
## Working on eta = 50
## Working on eta = 40
## Working on eta = 30
## Working on eta = 20
## Working on eta = 15
## Working on eta = 14
## Working on eta = 13
## Working on eta = 12
## Working on eta = 11
## Working on eta = 10
## Working on eta = 9
## Working on eta = 8
## Working on eta = 7
## Working on eta = 6
## Working on eta = 5
## Working on eta = 4
## Working on eta = 3
## Working on eta = 2
## Working on eta = 1res.df = as.data.frame(do.call("rbind",res.list))
ggplot( data = res.df, aes( x = eta, y = est ) ) +
geom_ribbon( data = res.df, aes( x = eta, ymin = lo, ymax = hi ), fill = "gray" ) +
geom_line( lwd = 1.2 ) +
xlab( bquote( eta ) ) +
ylab( bquote( hat(mu)[eta] ) ) +
theme_classic()
significance_funnel
significance_funnel(
ma_data$d_calc,
ma_data$d_var_calc,
xmin = min(ma_data$d_calc),
xmax = max(ma_data$d_calc),
ymin = 0,
ymax = max(sqrt(ma_data$d_var_calc)),
xlab = "Point estimate",
ylab = "Estimated standard error",
favor.positive = TRUE,
est.all = NA,
est.N = NA,
alpha.select = 0.05,
plot.pooled = TRUE
)
Estimate the S_val
But it is impossible to attenuate the pooled point estimate to 0.
sval <- data.frame()
for (i in seq(0, 0.1, by = 0.02)){
s <- svalue(
ma_data$d_calc,
ma_data$d_var_calc,
q = i,
clustervar = 1:length(ma_data$d_calc),
model = "robust",
alpha.select = 0.05,
eta.grid.hi = 200,
favor.positive = TRUE,
CI.level = 0.95,
small = TRUE,
return.worst.meta = FALSE
)
s <- s %>% mutate(q_val = i)
print(s)
#sval <- bind_rows(sval, s)
}## sval.est sval.ci k.affirmative k.nonaffirmative signs.recoded q_val
## 1 Not possible 3.330065 17 43 FALSE 0
## sval.est sval.ci k.affirmative k.nonaffirmative signs.recoded q_val
## 1 Not possible 2.589983 17 43 FALSE 0.02
## sval.est sval.ci k.affirmative k.nonaffirmative signs.recoded q_val
## 1 Not possible 2.086418 17 43 FALSE 0.04
## sval.est sval.ci k.affirmative k.nonaffirmative signs.recoded q_val
## 1 33.4207 1.723167 17 43 FALSE 0.06
## sval.est sval.ci k.affirmative k.nonaffirmative signs.recoded q_val
## 1 10.04648 1.449971 17 43 FALSE 0.08
## sval.est sval.ci k.affirmative k.nonaffirmative signs.recoded q_val
## 1 5.796755 1.237981 17 43 FALSE 0.1sval## data frame with 0 columns and 0 rowsma_data## coder unique_id
## 1 alana/anjie arunachalam2010
## 2 alana/anjie arunachalam2010
## 3 alana/anjie arunachalam2013b
## 4 alana/anjie arunachalam2013b
## 5 anjie arunachalam2013c
## 6 anjie arunachalam2013c
## 7 anjie arunachalam2019
## 8 anjie arunachalam2019
## 9 anjie arunachalam2019
## 10 anjie arunachalam2019
## 11 anjie hirsh-pasek1996
## 12 anjie/molly gertner2012
## 13 anjie/molly gertner2012
## 14 anjie/molly gertner2012
## 15 anjie gertner2012
## 16 anjie gertner2012
## 17 anjie gertner2012
## 18 anjie gertner2012
## 19 anjie gertner2012
## 20 anjie he2020
## 21 anjie he2020
## 22 izzy jin2015
## 23 izzy jin2015
## 24 izzy jin2015
## 25 izzy jin2015
## 26 izzy jin2015
## 27 izzy jin2015
## 28 izzy jin2015
## 29 izzy jin2015
## 30 anjie jin2015
## 31 anjie jin2015
## 32 anjie jin2015
## 33 anjie jin2015
## 34 anjie jyotishi
## 35 anjie jyotishi
## 36 izzy messenger2014
## 37 izzy messenger2014
## 38 anjie naigles_unpublished_visit5
## 39 anjie naigles_unpublished_visit6
## 40 anjie naigles1990
## 41 anjie naigles1990
## 42 maya/anjie naigles1993
## 43 maya/anjie naigles1993
## 44 maya/anjie naigles2011
## 45 anjie scott2017
## 46 anjie scott2017
## 47 anjie yuan2009a
## 48 anjie yuan2009a
## 49 anjie yuan2009a
## 50 anjie yuan2009a
## 51 anjie yuan2012
## 52 anjie yuan2012
## 53 anjie yuan2012
## 54 anjie yuan2012
## 55 anjie yuan2012
## 56 anjie yuan2012
## 57 anjie yuan2012
## 58 anjie yuan2012
## 59 anjie yuan2012
## 60 anjie yuan2012
## long_cite
## 1 Arunachalam, S., & Waxman, S. R. (2010). Meaning from syntax: Evidence from 2-year-olds. Cognition, 114(3), 442-446.
## 2 Arunachalam, S., & Waxman, S. R. (2010). Meaning from syntax: Evidence from 2-year-olds. Cognition, 114(3), 442-446.
## 3 Arunachalam, S. (2013). Two-year-olds can begin to acquire verb meanings in socially impoverished contexts. Cognition, 129(3), 569-573.
## 4 Arunachalam, S. (2013). Two-year-olds can begin to acquire verb meanings in socially impoverished contexts. Cognition, 129(3), 569-573.
## 5 Arunachalam, S., Escovar, E., Hansen, M. A., & Waxman, S. R. (2013). Out of sight, but not out of mind: 21-month-olds use syntactic information to learn verbs even in the absence of a corresponding event. Language and cognitive processes, 28(4), 417-425.
## 6 Arunachalam, S., Escovar, E., Hansen, M. A., & Waxman, S. R. (2013). Out of sight, but not out of mind: 21-month-olds use syntactic information to learn verbs even in the absence of a corresponding event. Language and cognitive processes, 28(4), 417-425.
## 7 Arunachalam, S., & Dennis, S. (2019). Semantic detail in the developing verb lexicon: An extension of Naigles and Kako (1993). Developmental science, 22(1), e12697.
## 8 Arunachalam, S., & Dennis, S. (2019). Semantic detail in the developing verb lexicon: An extension of Naigles and Kako (1993). Developmental science, 22(1), e12697.
## 9 Arunachalam, S., & Dennis, S. (2019). Semantic detail in the developing verb lexicon: An extension of Naigles and Kako (1993). Developmental science, 22(1), e12697.
## 10 Arunachalam, S., & Dennis, S. (2019). Semantic detail in the developing verb lexicon: An extension of Naigles and Kako (1993). Developmental science, 22(1), e12697.
## 11 Hirsh-Pasek, K., Golinkoff, R. M., & Naigles, L. (1996). Young children’s use of syntactic frames to derive meaning. The origins of grammar: Evidence from early language comprehension, 123-158.
## 12 Gertner, Y., & Fisher, C. (2012). Predicted errors in children’s early sentence comprehension. Cognition, 124(1), 85-94.
## 13 Gertner, Y., & Fisher, C. (2012). Predicted errors in children’s early sentence comprehension. Cognition, 124(1), 85-94.
## 14 Gertner, Y., & Fisher, C. (2012). Predicted errors in children’s early sentence comprehension. Cognition, 124(1), 85-94.
## 15 Gertner, Y., & Fisher, C. (2012). Predicted errors in children’s early sentence comprehension. Cognition, 124(1), 85-94.
## 16 Gertner, Y., & Fisher, C. (2012). Predicted errors in children’s early sentence comprehension. Cognition, 124(1), 85-94.
## 17 Gertner, Y., & Fisher, C. (2012). Predicted errors in children’s early sentence comprehension. Cognition, 124(1), 85-94.
## 18 Gertner, Y., & Fisher, C. (2012). Predicted errors in children’s early sentence comprehension. Cognition, 124(1), 85-94.
## 19 Gertner, Y., & Fisher, C. (2012). Predicted errors in children’s early sentence comprehension. Cognition, 124(1), 85-94.
## 20 He, A. X., Huang, S., Waxman, S., & Arunachalam, S. (2020). Two-year-olds consolidate verb meanings during a nap. Cognition, 198, 104205.
## 21 He, A. X., Huang, S., Waxman, S., & Arunachalam, S. (2020). Two-year-olds consolidate verb meanings during a nap. Cognition, 198, 104205.
## 22 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 23 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 24 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 25 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 26 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 27 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 28 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 29 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 30 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 31 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 32 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 33 Jin, K. S. (2015). The role of syntactic and discourse information in verb learning (Doctoral dissertation, University of Illinois at Urbana-Champaign).
## 34 ???POSTER
## 35 ???POSTER
## 36 Messenger, K., Yuan, S., & Fisher, C. (2015). Learning verb syntax via listening: New evidence from 22-month-olds. Language Learning and Development, 11(4), 356-368.
## 37 Messenger, K., Yuan, S., & Fisher, C. (2015). Learning verb syntax via listening: New evidence from 22-month-olds. Language Learning and Development, 11(4), 356-368.
## 38 <NA>
## 39 <NA>
## 40 Naigles, Letitia. "Children use syntax to learn verb meanings." Journal of child language 17.2 (1990): 357-374.
## 41 Naigles, Letitia. "Children use syntax to learn verb meanings." Journal of child language 17.2 (1990): 357-374.
## 42 Naigles, L. G., & Kako, E. T. (1993). First contact in verb acquisition: Defining a role for syntax. Child development, 64(6), 1665-1687.
## 43 Naigles, L. G., & Kako, E. T. (1993). First contact in verb acquisition: Defining a role for syntax. Child development, 64(6), 1665-1687.
## 44 Naigles, L. R., Kelty, E., Jaffery, R., & Fein, D. (2011). Abstractness and continuity in the syntactic development of young children with autism. Autism Research, 4(6), 422-437.
## 45 Scott, K., Chu, J., & Schulz, L. (2017). Lookit (Part 2): Assessing the viability of online developmental research, results from three case studies. Open Mind, 1(1), 15-29.
## 46 Scott, K., Chu, J., & Schulz, L. (2017). Lookit (Part 2): Assessing the viability of online developmental research, results from three case studies. Open Mind, 1(1), 15-29.
## 47 Yuan, S., & Fisher, C. (2009). “Really? She blicked the baby?” Two-year-olds learn combinatorial facts about verbs by listening. Psychological science, 20(5), 619-626.
## 48 Yuan, S., & Fisher, C. (2009). “Really? She blicked the baby?” Two-year-olds learn combinatorial facts about verbs by listening. Psychological science, 20(5), 619-626.
## 49 Yuan, S., & Fisher, C. (2009). “Really? She blicked the baby?” Two-year-olds learn combinatorial facts about verbs by listening. Psychological science, 20(5), 619-626.
## 50 Yuan, S., & Fisher, C. (2009). “Really? She blicked the baby?” Two-year-olds learn combinatorial facts about verbs by listening. Psychological science, 20(5), 619-626.
## 51 Yuan, S., Fisher, C., & Snedeker, J. (2012). Counting the nouns: Simple structural cues to verb meaning. Child development, 83(4), 1382-1399.
## 52 Yuan, S., Fisher, C., & Snedeker, J. (2012). Counting the nouns: Simple structural cues to verb meaning. Child development, 83(4), 1382-1399.
## 53 Yuan, S., Fisher, C., & Snedeker, J. (2012). Counting the nouns: Simple structural cues to verb meaning. Child development, 83(4), 1382-1399.
## 54 Yuan, S., Fisher, C., & Snedeker, J. (2012). Counting the nouns: Simple structural cues to verb meaning. Child development, 83(4), 1382-1399.
## 55 Yuan, S., Fisher, C., & Snedeker, J. (2012). Counting the nouns: Simple structural cues to verb meaning. Child development, 83(4), 1382-1399.
## 56 Yuan, S., Fisher, C., & Snedeker, J. (2012). Counting the nouns: Simple structural cues to verb meaning. Child development, 83(4), 1382-1399.
## 57 Yuan, S., Fisher, C., & Snedeker, J. (2012). Counting the nouns: Simple structural cues to verb meaning. Child development, 83(4), 1382-1399.
## 58 Yuan, S., Fisher, C., & Snedeker, J. (2012). Counting the nouns: Simple structural cues to verb meaning. Child development, 83(4), 1382-1399.
## 59 Yuan, S., Fisher, C., & Snedeker, J. (2012). Counting the nouns: Simple structural cues to verb meaning. Child development, 83(4), 1382-1399.
## 60 Yuan, S., Fisher, C., & Snedeker, J. (2012). Counting the nouns: Simple structural cues to verb meaning. Child development, 83(4), 1382-1399.
## link
## 1 https://www.sciencedirect.com/science/article/abs/pii/S0010027709002674
## 2 https://www.sciencedirect.com/science/article/abs/pii/S0010027709002674
## 3 https://www.sciencedirect.com/science/article/pii/S0010027713001789
## 4 https://www.sciencedirect.com/science/article/pii/S0010027713001789
## 5 https://www.tandfonline.com/doi/full/10.1080/01690965.2011.641744
## 6 https://www.tandfonline.com/doi/full/10.1080/01690965.2011.641744
## 7 https://onlinelibrary.wiley.com/doi/pdf/10.1111/desc.12697
## 8 https://onlinelibrary.wiley.com/doi/pdf/10.1111/desc.12697
## 9 https://onlinelibrary.wiley.com/doi/pdf/10.1111/desc.12697
## 10 https://onlinelibrary.wiley.com/doi/pdf/10.1111/desc.12697
## 11 https://drive.google.com/file/d/1232E8hBQHPpchgAT2P3wJ2gnSwKlDgza/view
## 12 https://www.sciencedirect.com/science/article/abs/pii/S0010027712000601
## 13 https://www.sciencedirect.com/science/article/abs/pii/S0010027712000601
## 14 https://www.sciencedirect.com/science/article/abs/pii/S0010027712000601
## 15 https://www.sciencedirect.com/science/article/abs/pii/S0010027712000601
## 16 https://www.sciencedirect.com/science/article/abs/pii/S0010027712000601
## 17 https://www.sciencedirect.com/science/article/abs/pii/S0010027712000601
## 18 https://www.sciencedirect.com/science/article/abs/pii/S0010027712000601
## 19 https://www.sciencedirect.com/science/article/abs/pii/S0010027712000601
## 20 https://reader.elsevier.com/reader/sd/pii/S001002772030024X?token=02503878CEB15BF77278EC5C399C67DB6C05F24619E47B377C90E3E161E184F5CD606796ACFC2D3E4871B90D3BE46E5C
## 21 https://reader.elsevier.com/reader/sd/pii/S001002772030024X?token=02503878CEB15BF77278EC5C399C67DB6C05F24619E47B377C90E3E161E184F5CD606796ACFC2D3E4871B90D3BE46E5C
## 22 https://www.ideals.illinois.edu/handle/2142/78435
## 23 https://www.ideals.illinois.edu/handle/2142/78436
## 24 https://www.ideals.illinois.edu/handle/2142/78437
## 25 https://www.ideals.illinois.edu/handle/2142/78438
## 26 https://www.ideals.illinois.edu/handle/2142/78437
## 27 https://www.ideals.illinois.edu/handle/2142/78438
## 28 https://www.ideals.illinois.edu/handle/2142/78439
## 29 https://www.ideals.illinois.edu/handle/2142/78440
## 30 https://www.ideals.illinois.edu/handle/2142/78440
## 31 https://www.ideals.illinois.edu/handle/2142/78440
## 32 https://www.ideals.illinois.edu/handle/2142/78440
## 33 https://www.ideals.illinois.edu/handle/2142/78440
## 34 POSTER
## 35 POSTER
## 36 https://www.tandfonline.com/doi/full/10.1080/15475441.2014.978331?scroll=top&needAccess=true
## 37 https://www.tandfonline.com/doi/full/10.1080/15475441.2014.978331?scroll=top&needAccess=true
## 38 unpublished_data
## 39 unpublished_data
## 40 https://www.cambridge.org/core/journals/journal-of-child-language/article/children-use-syntax-to-learn-verb-meanings/4E19981CDD2D247CBB37D32A45BAFE31
## 41 https://www.cambridge.org/core/journals/journal-of-child-language/article/children-use-syntax-to-learn-verb-meanings/4E19981CDD2D247CBB37D32A45BAFE31
## 42 https://www.jstor.org/stable/pdf/1131462.pdf?seq=2
## 43 https://www.jstor.org/stable/pdf/1131462.pdf?seq=3
## 44 https://onlinelibrary.wiley.com/doi/full/10.1002/aur.223?casa_token=Gny81KxMUrQAAAAA%3Adhn9dMHKXEwe1lAgt2RHsmj5fErzaV97YT5ad20C-S_-Op9-RR5jmfF9zq42yzO5IcFE133jdnM
## 45 https://www.mitpressjournals.org/doi/full/10.1162/OPMI_a_00001
## 46 https://www.mitpressjournals.org/doi/full/10.1162/OPMI_a_00001
## 47 https://journals.sagepub.com/doi/abs/10.1111/j.1467-9280.2009.02341.x
## 48 https://journals.sagepub.com/doi/abs/10.1111/j.1467-9280.2009.02341.x
## 49 https://journals.sagepub.com/doi/abs/10.1111/j.1467-9280.2009.02341.x
## 50 https://journals.sagepub.com/doi/abs/10.1111/j.1467-9280.2009.02341.x
## 51 https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-8624.2012.01783.x?casa_token=L0uY-e1_C9sAAAAA%3AzP8_NodiA0Z5TaR4sfXCXxhhXOkp63eKDs0p2ofpNhOEj52lWyR9-FNbNd7e1CVBm1rlv3ZG0Y8
## 52 https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-8624.2012.01783.x?casa_token=L0uY-e1_C9sAAAAA%3AzP8_NodiA0Z5TaR4sfXCXxhhXOkp63eKDs0p2ofpNhOEj52lWyR9-FNbNd7e1CVBm1rlv3ZG0Y8
## 53 https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-8624.2012.01783.x?casa_token=L0uY-e1_C9sAAAAA%3AzP8_NodiA0Z5TaR4sfXCXxhhXOkp63eKDs0p2ofpNhOEj52lWyR9-FNbNd7e1CVBm1rlv3ZG0Y8
## 54 https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-8624.2012.01783.x?casa_token=L0uY-e1_C9sAAAAA%3AzP8_NodiA0Z5TaR4sfXCXxhhXOkp63eKDs0p2ofpNhOEj52lWyR9-FNbNd7e1CVBm1rlv3ZG0Y8
## 55 https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-8624.2012.01783.x?casa_token=L0uY-e1_C9sAAAAA%3AzP8_NodiA0Z5TaR4sfXCXxhhXOkp63eKDs0p2ofpNhOEj52lWyR9-FNbNd7e1CVBm1rlv3ZG0Y8
## 56 https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-8624.2012.01783.x?casa_token=L0uY-e1_C9sAAAAA%3AzP8_NodiA0Z5TaR4sfXCXxhhXOkp63eKDs0p2ofpNhOEj52lWyR9-FNbNd7e1CVBm1rlv3ZG0Y8
## 57 https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-8624.2012.01783.x?casa_token=L0uY-e1_C9sAAAAA%3AzP8_NodiA0Z5TaR4sfXCXxhhXOkp63eKDs0p2ofpNhOEj52lWyR9-FNbNd7e1CVBm1rlv3ZG0Y8
## 58 https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-8624.2012.01783.x?casa_token=L0uY-e1_C9sAAAAA%3AzP8_NodiA0Z5TaR4sfXCXxhhXOkp63eKDs0p2ofpNhOEj52lWyR9-FNbNd7e1CVBm1rlv3ZG0Y8
## 59 https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-8624.2012.01783.x?casa_token=L0uY-e1_C9sAAAAA%3AzP8_NodiA0Z5TaR4sfXCXxhhXOkp63eKDs0p2ofpNhOEj52lWyR9-FNbNd7e1CVBm1rlv3ZG0Y8
## 60 https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/j.1467-8624.2012.01783.x?casa_token=L0uY-e1_C9sAAAAA%3AzP8_NodiA0Z5TaR4sfXCXxhhXOkp63eKDs0p2ofpNhOEj52lWyR9-FNbNd7e1CVBm1rlv3ZG0Y8
## grammatical_class paper_eligibility
## 1 verb include
## 2 verb include
## 3 verb include
## 4 verb include
## 5 verb include
## 6 verb include
## 7 verb include
## 8 verb include
## 9 verb include
## 10 verb include
## 11 verb include
## 12 verb include
## 13 verb include
## 14 verb include
## 15 verb include
## 16 verb include
## 17 verb include
## 18 verb include
## 19 verb include
## 20 verb include
## 21 verb include
## 22 verb include
## 23 verb include
## 24 verb include
## 25 verb include
## 26 verb include
## 27 verb include
## 28 verb include
## 29 verb include
## 30 verb include
## 31 verb include
## 32 verb include
## 33 verb include
## 34 verb include
## 35 verb include
## 36 verb include
## 37 verb include
## 38 verb include
## 39 verb include
## 40 verb include
## 41 verb include
## 42 verb include
## 43 verb include
## 44 verb include
## 45 verb include
## 46 verb include
## 47 verb include
## 48 verb include
## 49 verb include
## 50 verb include
## 51 verb include
## 52 verb include
## 53 verb include
## 54 verb include
## 55 verb include
## 56 verb include
## 57 verb include
## 58 verb include
## 59 verb include
## 60 verb include
## short_cite
## 1 Arunachalam, S., & Waxman, S. R. (2010)
## 2 Arunachalam, S., & Waxman, S. R. (2010)
## 3 Arunachalam, S. (2013)
## 4 Arunachalam, S. (2013)
## 5 Arunachalam, S., Escovar, E., Hansen, M. A., & Waxman, S. R. (2013)
## 6 Arunachalam, S., Escovar, E., Hansen, M. A., & Waxman, S. R. (2013)
## 7 Arunachalam, S., & Dennis, S. (2019)
## 8 Arunachalam, S., & Dennis, S. (2019)
## 9 Arunachalam, S., & Dennis, S. (2019)
## 10 Arunachalam, S., & Dennis, S. (2019)
## 11 Hirsh-Pasek, K., Golinkoff, R. M., & Naigles, L. (1996)
## 12 Gertner, Y., & Fisher, C. (2012)
## 13 Gertner, Y., & Fisher, C. (2012)
## 14 Gertner, Y., & Fisher, C. (2012)
## 15 Gertner, Y., & Fisher, C. (2012)
## 16 Gertner, Y., & Fisher, C. (2012)
## 17 Gertner, Y., & Fisher, C. (2012)
## 18 Gertner, Y., & Fisher, C. (2012)
## 19 Gertner, Y., & Fisher, C. (2012)
## 20 He, A. X., Huang, S., Waxman, S., & Arunachalam, S. (2020).
## 21 He, A. X., Huang, S., Waxman, S., & Arunachalam, S. (2020).
## 22 Jin, K. S. (2015)
## 23 Jin, K. S. (2015)
## 24 Jin, K. S. (2015)
## 25 Jin, K. S. (2015)
## 26 Jin, K. S. (2015)
## 27 Jin, K. S. (2015)
## 28 Jin, K. S. (2015)
## 29 Jin, K. S. (2015)
## 30 Jin, K. S. (2015)
## 31 Jin, K. S. (2015)
## 32 Jin, K. S. (2015)
## 33 Jin, K. S. (2015)
## 34 Jyotishi & Naigles, Poster
## 35 Jyotishi & Naigles, Poster
## 36 Messenger, K., Yuan, S., & Fisher, C. (2015)
## 37 Messenger, K., Yuan, S., & Fisher, C. (2015)
## 38 Naigles, unpublished data, visit 5
## 39 Naigles, unpublished data, visit 6
## 40 Naigles, L.(1990).
## 41 Naigles, L.(1990).
## 42 Naigles, L. G., & Kako, E.T. (1993).
## 43 Naigles, L. G., & Kako, E.T. (1993).
## 44 Naigles, L. R., Kelty, E., Jaffery, R., & Fein, D. (2011).
## 45 Scott, K., Chu, J., & Schulz, L. (2017)
## 46 Scott, K., Chu, J., & Schulz, L. (2017)
## 47 Yuan, S., & Fisher, C. (2009).
## 48 Yuan, S., & Fisher, C. (2009).
## 49 Yuan, S., & Fisher, C. (2009).
## 50 Yuan, S., & Fisher, C. (2009).
## 51 Yuan, S., Fisher, C., & Snedeker, J. (2012)
## 52 Yuan, S., Fisher, C., & Snedeker, J. (2012)
## 53 Yuan, S., Fisher, C., & Snedeker, J. (2012)
## 54 Yuan, S., Fisher, C., & Snedeker, J. (2012)
## 55 Yuan, S., Fisher, C., & Snedeker, J. (2012)
## 56 Yuan, S., Fisher, C., & Snedeker, J. (2012)
## 57 Yuan, S., Fisher, C., & Snedeker, J. (2012)
## 58 Yuan, S., Fisher, C., & Snedeker, J. (2012)
## 59 Yuan, S., Fisher, C., & Snedeker, J. (2012)
## 60 Yuan, S., Fisher, C., & Snedeker, J. (2012)
## data_source expt_num plot_label
## 1 results_text 1 Arunachalam & Waxman (2010) - 1a
## 2 results_text 1 Arunachalam & Waxman (2010) - 1b
## 3 results_text 1 Arunachalam (2013) - 1a
## 4 results_text 1 Arunachalam (2013) - 1b
## 5 imputed 1 Arunachalam, Escovar, Hansen, & Waxman, (2013) - 1a
## 6 imputed 1 Arunachalam, Escovar, Hansen, & Waxman, (2013) - 1b
## 7 author_contact 1 Arunachalam & Dennis (2019) - 1a
## 8 author_contact 1 Arunachalam & Dennis (2019) - 1b
## 9 author_contact 2 Arunachalam & Dennis (2019) - 2a
## 10 author_contact 2 Arunachalam & Dennis (2019) - 2b
## 11 imputed 6 Hirsh-Pasek, Golinkoff, & Naigles, (1996) - 6a
## 12 figure_6 1 Gertner & Fisher (2012) - 1a
## 13 figure_6 1 Gertner & Fisher (2012) - 1b
## 14 figure_6 1 Gertner & Fisher (2012) - 1c
## 15 results_text 1 Gertner & Fisher (2012) - 1d
## 16 results_text 1 Gertner & Fisher (2012) - 1e
## 17 figure_6 2 Gertner & Fisher (2012) - 2a
## 18 figure_6 2 Gertner & Fisher (2012) - 2b
## 19 figure_6 2 Gertner & Fisher (2012) - 2c
## 20 results_text 1 He, Huang, Waxman, & Arunachalam (2020) - 1a
## 21 results_text 1 He, Huang, Waxman, & Arunachalam (2020) - 1b
## 22 results_text 1 Jin (2015) - 1a
## 23 results_text 1 Jin (2015) - 1b
## 24 results_text 1 Jin (2015) - 1c
## 25 results_text 1 Jin (2015) - 1d
## 26 results_text 2 Jin (2015) - 2a
## 27 results_text 2 Jin (2015) - 2b
## 28 results_text 3 Jin (2015) - 3a
## 29 results_text 3 Jin (2015) - 3b
## 30 results_text 6 Jin (2015) - 6a
## 31 table_3 7 Jin (2015) - 6b
## 32 results_text 8 Jin (2015) - 6c
## 33 results_text 8 Jin (2015) - 6d
## 34 results_figure 1 Jyotishi & Naigles, poster - 1a
## 35 results_figure 1 Jyotishi & Naigles, poster - 1b
## 36 figure_2 1 Messenger, Yuan, & Fisher (2015) - 1a
## 37 figure_2 1 Messenger, Yuan, & Fisher (2015) - 1b
## 38 author_contact visit5 Naigles, unpublished - v5
## 39 author_contact visit6 Naigles, unpublished - v6
## 40 contact_author 1 Naigles (1990) - 1a
## 41 contact_author 1 Naigles (1990) - 1b
## 42 results_text 2 Naigles & Kako (1993) - 2a
## 43 results_text 2 Naigles & Kako (1993) - 2b
## 44 table_vi 1 Naigles, Kelty, Jaffery, & Fein (2011) - 1a
## 45 author_contact 2 Scott, Chu, & Schulz (2017) - 2a
## 46 author_contact 2 Scott, Chu, & Schulz (2017) - 2b
## 47 table_1 1 Yuan & Fisher (2009) - 1a
## 48 table_1 1 Yuan & Fisher (2009) - 1b
## 49 table_2 2 Yuan & Fisher (2009) - 2a
## 50 table_2 2 Yuan & Fisher (2009) - 2b
## 51 results_text 1 Yuan, Fisher, & Snedeker (2012) - 1a
## 52 results_text 1 Yuan, Fisher, & Snedeker (2012) - 1b
## 53 results_text 1_rep Yuan, Fisher, & Snedeker (2012) - 1c
## 54 results_text 1_rep Yuan, Fisher, & Snedeker (2012) - 1d
## 55 results_text 2 Yuan, Fisher, & Snedeker (2012) - 2a
## 56 results_text 2 Yuan, Fisher, & Snedeker (2012) - 2b
## 57 results_text 3 Yuan, Fisher, & Snedeker (2012) - 3a
## 58 results_text 3 Yuan, Fisher, & Snedeker (2012) - 3b
## 59 results_text 3 Yuan, Fisher, & Snedeker (2012) - 3c
## 60 results_text 3 Yuan, Fisher, & Snedeker (2012) - 3d
## expt_condition dependent_measure response_mode
## 1 transitive point_scene behavior
## 2 intransitive point_scene behavior
## 3 transitive looking_duration eye_tracking
## 4 intransitive looking_duration eye_tracking
## 5 transitive looking_duration eye_tracking
## 6 intransitive looking_duration eye_tracking
## 7 transitive looking_duration eye_tracking
## 8 intransitive looking_duration eye_tracking
## 9 transitive looking_duration eye_tracking
## 10 intransitive looking_duration eye_tracking
## 11 transitive looking_duration looking
## 12 transitive_sentence looking_duration looking
## 13 agent_first looking_duration looking
## 14 patient_first looking_duration looking
## 15 transitive_sentence looking_duration looking
## 16 agent_first looking_duration looking
## 17 transitive_sentence looking_duration looking
## 18 agent_first looking_duration looking
## 19 patient_first looking_duration looking
## 20 wake_condition_visit1 looking_duration looking
## 21 nap_condition_visit1 looking_duration looking
## 22 no_bystander_transitive looking_duration looking
## 23 no_bystander_intransitive looking_duration looking
## 24 no_bystander_transitive_ rep looking_duration looking
## 25 no_bystander_intransitive_rep looking_duration looking
## 26 bystander_transitive looking_duration looking
## 27 bystander_intransitive looking_duration looking
## 28 it_transitive looking_duration looking
## 29 it_intransitive looking_duration looking
## 30 same_verb_intransitive looking_duration looking
## 31 coherent_intransitive looking_duration looking
## 32 coherent_intransitive_2 looking_duration looking
## 33 coherent_intransitive_3 looking_duration looking
## 34 transitive looking_duration looking
## 35 intransitive looking_duration looking
## 36 same_transitive looking_duration looking
## 37 same_intransitive looking_duration looking
## 38 transitive looking_duration looking
## 39 transitive looking_duration looking
## 40 transitive looking_duration looking
## 41 intransitive looking_duration looking
## 42 transitive_sentence looking_duration looking
## 43 intransitive_sentence looking_duration looking
## 44 transitive_intransitive looking_duration looking
## 45 transitive_experiment looking_duration looking
## 46 intransitive_experiment looking_duration looking
## 47 transitive_sentence looking_duration looking
## 48 intransitive_sentence looking_duration looking
## 49 transitive_sentence_same_day looking_duration looking
## 50 intransitive_sentence_same_day looking_duration looking
## 51 transitive_sentence_simple_event looking_duration looking
## 52 intransitive_sentence_simple_event looking_duration looking
## 53 transitive_sentence_simple_event looking_duration looking
## 54 intransitive_sentence_bystander_event looking_duration looking
## 55 transitive_sentence_bystander_event looking_duration looking
## 56 intransitive_sentence_bystander_event looking_duration looking
## 57 transitive_simple_events looking_duration looking
## 58 intransitive_simple_events looking_duration looking
## 59 transitive_sentence_bystander_event looking_duration looking
## 60 intransitive_sentence_bystander_event looking_duration looking
## test_type se same_infant language mean_age productive_vocab_mean
## 1 action NA 1 English 831.0120 442.00
## 2 action NA 2 English 831.0120 442.00
## 3 action NA 3 English 827.9680 75.00
## 4 action NA 4 English 827.9680 75.00
## 5 action NA 5 English 645.3280 NA
## 6 action NA 6 English 645.3280 NA
## 7 action NA 7 English 831.0120 NA
## 8 action NA 8 English 831.0120 NA
## 9 action NA 9 English 851.2000 NA
## 10 action NA 10 English 851.2000 NA
## 11 action NA 11 English 882.7600 NA
## 12 action 0.05833333 12 English 627.0640 NA
## 13 action 0.03611111 13 English 627.0640 NA
## 14 action 0.04722222 14 English 627.0640 NA
## 15 action 0.03000000 15 English 940.5960 NA
## 16 action 0.05000000 16 English 940.5960 NA
## 17 action 0.02638889 17 English 633.1520 NA
## 18 action 0.01944444 18 English 633.1520 NA
## 19 action 0.03194444 19 English 633.1520 NA
## 20 action NA 20 English 815.7920 NA
## 21 action NA 21 English 815.7920 NA
## 22 action NA 22 English 471.8200 NA
## 23 action NA 23 English 471.8200 NA
## 24 action NA 24 English 453.5560 NA
## 25 action NA 25 English 453.5560 NA
## 26 action NA 26 English 471.8200 NA
## 27 action NA 27 English 471.8200 NA
## 28 action NA 28 English 578.3600 NA
## 29 action NA 29 English 578.3600 NA
## 30 action NA 30 English 1269.3480 NA
## 31 action NA 31 English 1217.6000 NA
## 32 action NA 32 English 992.3440 NA
## 33 action NA 33 English 1278.4800 NA
## 34 action NA naigles2011 English 875.1500 456.06
## 35 action NA naigles2011 English 875.1500 456.06
## 36 action NA 36 English 684.9000 NA
## 37 action NA 37 English 684.9000 NA
## 38 action NA naigles2011 English 1117.7568 NA
## 39 action NA naigles2011 English 1246.8224 NA
## 40 action NA 40 English 761.0000 NA
## 41 action NA 41 English 761.0000 NA
## 42 action NA 42 English 852.3200 NA
## 43 action NA 43 English 791.4400 NA
## 44 action NA naigles2011 English 626.7596 118.77
## 45 action NA 45 English 888.8480 NA
## 46 action NA 46 English 888.8480 NA
## 47 action 0.05591678 47 English 870.5840 NA
## 48 action 0.05369128 48 English 870.5840 NA
## 49 action 0.04941482 49 English 864.4960 NA
## 50 action 0.02638889 50 English 864.4960 NA
## 51 action NA 51 English 648.3720 NA
## 52 action NA 52 English 648.3720 NA
## 53 action NA 53 English 648.3720 NA
## 54 action NA 54 English 648.3720 NA
## 55 action NA 55 English 630.1080 NA
## 56 action NA 56 English 630.1080 NA
## 57 action NA 57 English 572.2720 NA
## 58 action NA 58 English 572.2720 NA
## 59 action NA 59 English 572.2720 NA
## 60 action NA 60 English 572.2720 NA
## productive_vocab_median population_type sentence_structure
## 1 NA typically_developing transitive
## 2 NA typically_developing intransitive
## 3 NA typically_developing transitive
## 4 NA typically_developing intransitive
## 5 NA typically_developing transitive
## 6 NA typically_developing intransitive
## 7 72.0 typically_developing transitive
## 8 80.0 typically_developing intransitive
## 9 80.0 typically_developing transitive
## 10 73.0 typically_developing intransitive
## 11 NA typically_developing transitive
## 12 28.0 typically_developing transitive
## 13 28.0 typically_developing intransitive
## 14 28.0 typically_developing intransitive
## 15 NA typically_developing transitive
## 16 NA typically_developing intransitive
## 17 29.5 typically_developing transitive
## 18 29.5 typically_developing intransitive
## 19 29.5 typically_developing intransitive
## 20 NA typically_developing transitive
## 21 NA typically_developing transitive
## 22 NA typically_developing transitive
## 23 NA typically_developing intransitive
## 24 NA typically_developing transitive
## 25 NA typically_developing intransitive
## 26 NA typically_developing transitive
## 27 NA typically_developing intransitive
## 28 17.0 typically_developing transitive
## 29 17.0 typically_developing intransitive
## 30 90.0 typically_developing intransitive
## 31 81.0 typically_developing intransitive
## 32 59.0 typically_developing intransitive
## 33 82.5 typically_developing intransitive
## 34 NA typically_developing transitive
## 35 NA typically_developing intransitive
## 36 38.0 typically_developing transitive
## 37 38.0 typically_developing intransitive
## 38 NA typically_developing transitive
## 39 NA typically_developing transitive
## 40 NA typically_developing transitive
## 41 NA typically_developing intransitive
## 42 NA typically_developing transitive
## 43 NA typically_developing intransitive
## 44 NA typically_developing transitive
## 45 NA typically_developing transitive
## 46 NA typically_developing intransitive
## 47 78.5 typically_developing transitive
## 48 78.5 typically_developing intransitive
## 49 72.5 typically_developing transitive
## 50 72.5 typically_developing intransitive
## 51 30.0 typically_developing transitive
## 52 30.0 typically_developing intransitive
## 53 54.5 typically_developing transitive
## 54 54.5 typically_developing intransitive
## 55 26.5 typically_developing transitive
## 56 26.5 typically_developing intransitive
## 57 16.0 typically_developing transitive
## 58 16.0 typically_developing intransitive
## 59 16.0 typically_developing transitive
## 60 16.0 typically_developing intransitive
## agent_argument_type patient_argument_type verb_type stimuli_type
## 1 pronoun pronoun fake_verb video_person
## 2 pronoun INTRANSITIVE fake_verb video_person
## 3 noun noun fake_verb video_person
## 4 noun INTRANSITIVE fake_verb video_person
## 5 pronoun pronoun fake_verb video_person
## 6 pronoun INTRANSITIVE fake_verb video_person
## 7 noun noun fake_verb video_person
## 8 noun INTRANSITIVE fake_verb video_person
## 9 pronoun pronoun fake_verb video_person
## 10 pronoun INTRANSITIVE fake_verb video_person
## 11 noun noun fake_verb video_non_person
## 12 noun noun fake_verb video_person
## 13 noun INTRANSITIVE fake_verb video_person
## 14 noun INTRANSITIVE fake_verb video_person
## 15 noun noun fake_verb video_person
## 16 noun INTRANSITIVE fake_verb video_person
## 17 noun noun fake_verb video_person
## 18 noun INTRANSITIVE fake_verb video_person
## 19 noun INTRANSITIVE fake_verb video_person
## 20 noun noun fake_verb video_person
## 21 noun noun fake_verb video_person
## 22 pronoun noun fake_verb animation_shape
## 23 pronoun INTRANSITIVE fake_verb animation_shape
## 24 pronoun noun fake_verb animation_shape
## 25 pronoun INTRANSITIVE fake_verb animation_shape
## 26 pronoun noun fake_verb animation_shape
## 27 pronoun INTRANSITIVE fake_verb animation_shape
## 28 pronoun noun fake_verb animation_shape
## 29 pronoun INTRANSITIVE fake_verb animation_shape
## 30 pronoun INTRANSITIVE fake_verb video_person
## 31 pronoun INTRANSITIVE fake_verb video_person
## 32 pronoun INTRANSITIVE fake_verb video_person
## 33 pronoun INTRANSITIVE fake_verb video_person
## 34 noun noun fake_verb video_person
## 35 noun INTRANSITIVE fake_verb video_person
## 36 pronoun noun fake_verb video_person
## 37 pronoun INTRANSITIVE fake_verb video_person
## 38 noun noun fake_verb video_person
## 39 noun noun fake_verb video_person
## 40 noun noun fake_verb video_non_person
## 41 noun INTRANSITIVE fake_verb video_non_person
## 42 noun noun fake_verb video_animal
## 43 noun INTRANSITIVE fake_verb video_animal
## 44 noun noun fake_verb video_animal
## 45 noun noun fake_verb video_person
## 46 noun INTRANSITIVE fake_verb video_person
## 47 pronoun noun fake_verb video_person
## 48 pronoun INTRANSITIVE fake_verb video_person
## 49 pronoun noun fake_verb video_person
## 50 pronoun INTRANSITIVE fake_verb video_person
## 51 pronoun pronoun fake_verb video_person
## 52 pronoun INTRANSITIVE fake_verb video_person
## 53 pronoun pronoun fake_verb video_person
## 54 pronoun INTRANSITIVE fake_verb video_person
## 55 pronoun pronoun fake_verb video_person
## 56 pronoun INTRANSITIVE fake_verb video_person
## 57 pronoun noun fake_verb video_person
## 58 pronoun INTRANSITIVE fake_verb video_person
## 59 pronoun noun fake_verb video_person
## 60 pronoun INTRANSITIVE fake_verb video_person
## stimuli_modality stimuli_actor transitive_event_type
## 1 video person direct_caused_action
## 2 video person direct_caused_action
## 3 video person direct_caused_action
## 4 video person direct_caused_action
## 5 video person direct_caused_action
## 6 video person direct_caused_action
## 7 video person direct_caused_action
## 8 video person direct_caused_action
## 9 video person direct_caused_action
## 10 video person direct_caused_action
## 11 video non_person direct_caused_action
## 12 video person indirect_caused_action
## 13 video person indirect_caused_action
## 14 video person indirect_caused_action
## 15 video person indirect_caused_action
## 16 video person indirect_caused_action
## 17 video person indirect_caused_action
## 18 video person indirect_caused_action
## 19 video person indirect_caused_action
## 20 video person direct_caused_action
## 21 video person direct_caused_action
## 22 animation non_person direct_caused_action
## 23 animation non_person direct_caused_action
## 24 animation non_person direct_caused_action
## 25 animation non_person direct_caused_action
## 26 animation non_person direct_caused_action
## 27 animation non_person direct_caused_action
## 28 animation non_person direct_caused_action
## 29 animation non_person direct_caused_action
## 30 video person indirect_caused_action
## 31 video person direct_caused_action
## 32 video person direct_caused_action
## 33 video person direct_caused_action
## 34 video non_person direct_caused_action
## 35 video non_person direct_caused_action
## 36 video person direct_caused_action
## 37 video person direct_caused_action
## 38 video non_person direct_caused_action
## 39 video non_person direct_caused_action
## 40 video non_person direct_caused_action
## 41 video non_person direct_caused_action
## 42 video non_person indirect_caused_action
## 43 video non_person indirect_caused_action
## 44 video non_person direct_caused_action
## 45 video person direct_caused_action
## 46 video person direct_caused_action
## 47 video person direct_caused_action
## 48 video person direct_caused_action
## 49 video person direct_caused_action
## 50 video person direct_caused_action
## 51 video person direct_caused_action
## 52 video person direct_caused_action
## 53 video person indirect_caused_action
## 54 video person indirect_caused_action
## 55 video person indirect_caused_action
## 56 video person indirect_caused_action
## 57 video person direct_caused_action
## 58 video person direct_caused_action
## 59 video person indirect_caused_action
## 60 video person indirect_caused_action
## intransitive_event_type presentation_type character_identification
## 1 parallel_actions asynchronous no
## 2 parallel_actions asynchronous no
## 3 parallel_actions asynchronous no
## 4 parallel_actions asynchronous no
## 5 parallel_actions asynchronous no
## 6 parallel_actions asynchronous no
## 7 parallel_actions immediate_after no
## 8 parallel_actions immediate_after no
## 9 parallel_actions asynchronous no
## 10 parallel_actions asynchronous no
## 11 parallel_actions immediate_after no
## 12 parallel_actions immediate_after yes
## 13 parallel_actions immediate_after yes
## 14 parallel_actions immediate_after yes
## 15 parallel_actions immediate_after yes
## 16 parallel_actions immediate_after yes
## 17 parallel_actions asynchronous yes
## 18 parallel_actions asynchronous yes
## 19 parallel_actions asynchronous yes
## 20 parallel_actions asynchronous no
## 21 parallel_actions asynchronous no
## 22 one_action asynchronous no
## 23 one_action asynchronous no
## 24 one_action asynchronous no
## 25 one_action asynchronous no
## 26 parallel_actions asynchronous no
## 27 parallel_actions asynchronous no
## 28 parallel_actions asynchronous no
## 29 parallel_actions asynchronous no
## 30 parallel_actions asynchronous no
## 31 parallel_actions asynchronous no
## 32 parallel_actions asynchronous no
## 33 parallel_actions asynchronous no
## 34 parallel_actions simultaneous yes
## 35 parallel_actions simultaneous yes
## 36 parallel_actions asynchronous no
## 37 parallel_actions asynchronous no
## 38 parallel_actions simultaneous yes
## 39 parallel_actions simultaneous yes
## 40 parallel_actions immediate_after yes
## 41 parallel_actions immediate_after yes
## 42 parallel_actions immediate_after yes
## 43 parallel_actions immediate_after yes
## 44 parallel_actions simultaneous no
## 45 one_action asynchronous no
## 46 one_action asynchronous no
## 47 one_action asynchronous no
## 48 one_action asynchronous no
## 49 one_action asynchronous no
## 50 one_action asynchronous no
## 51 one_action immediate_after no
## 52 one_action immediate_after no
## 53 one_action immediate_after no
## 54 one_action immediate_after no
## 55 parallel_actions immediate_after no
## 56 parallel_actions immediate_after no
## 57 one_action asynchronous no
## 58 one_action asynchronous no
## 59 parallel_actions asynchronous no
## 60 parallel_actions asynchronous no
## practice_phase test_mass_or_distributed n_train_test_pair
## 1 yes distributed 4
## 2 yes distributed 4
## 3 yes distributed 4
## 4 yes distributed 4
## 5 yes distributed 4
## 6 yes distributed 4
## 7 yes distributed 4
## 8 yes distributed 4
## 9 yes distributed 4
## 10 yes distributed 4
## 11 no distributed 4
## 12 yes distributed 2
## 13 yes distributed 2
## 14 yes distributed 2
## 15 yes distributed 2
## 16 yes distributed 2
## 17 yes distributed 2
## 18 yes distributed 2
## 19 yes distributed 2
## 20 no distributed 4
## 21 no distributed 4
## 22 no mass 1
## 23 no mass 1
## 24 no mass 1
## 25 no mass 1
## 26 no mass 1
## 27 no mass 1
## 28 no mass 1
## 29 no mass 1
## 30 yes mass 1
## 31 yes mass 1
## 32 yes mass 1
## 33 yes mass 1
## 34 no distributed 2
## 35 no distributed 2
## 36 yes mass 1
## 37 yes mass 1
## 38 no distributed 2
## 39 no distributed 2
## 40 no distributed 4
## 41 no distributed 4
## 42 no distributed 4
## 43 no distributed 4
## 44 no distributed 2
## 45 yes distributed 4
## 46 yes distributed 4
## 47 yes mass 1
## 48 yes mass 1
## 49 yes mass 1
## 50 yes mass 1
## 51 yes mass 1
## 52 yes mass 1
## 53 yes mass 1
## 54 yes mass 1
## 55 yes mass 1
## 56 yes mass 1
## 57 no mass 1
## 58 no mass 1
## 59 no mass 1
## 60 no mass 1
## n_test_trial_per_pair n_repetitions_sentence n_repetitions_video
## 1 1 8 2
## 2 1 8 2
## 3 1 27 2
## 4 1 27 2
## 5 1 8 2
## 6 1 8 2
## 7 1 1 3
## 8 1 1 3
## 9 1 8 2
## 10 1 8 2
## 11 1 4 4
## 12 2 5 2
## 13 2 5 2
## 14 2 5 2
## 15 2 5 2
## 16 2 5 2
## 17 2 21 2
## 18 2 21 2
## 19 2 21 2
## 20 1 8 2
## 21 1 8 2
## 22 2 17 2
## 23 2 17 2
## 24 2 17 2
## 25 2 17 2
## 26 2 17 2
## 27 2 17 2
## 28 3 13 3
## 29 3 13 3
## 30 3 10 3
## 31 1 12 1
## 32 1 12 1
## 33 1 12 1
## 34 2 3 6
## 35 2 3 6
## 36 2 16 2
## 37 2 16 2
## 38 2 3 6
## 39 2 3 6
## 40 2 3 6
## 41 2 3 6
## 42 2 3 6
## 43 2 3 6
## 44 2 3 6
## 45 2 12 3
## 46 2 12 3
## 47 2 8 2
## 48 2 8 2
## 49 3 12 3
## 50 3 12 3
## 51 2 5 2
## 52 2 5 2
## 53 2 5 2
## 54 2 5 2
## 55 2 7 2
## 56 2 7 2
## 57 2 14 2
## 58 2 14 2
## 59 3 18 3
## 60 3 18 3
## example_target_sentence
## 1 The lady mooped my brother / he is going to moop her
## 2 The lady and my brother mooped / Oh yes. They are going to moop
## 3 The girl wants to lorp the teacher
## 4 The girl and the teacher want to lorp
## 5 The lady mooped my brother / he is going to moop her
## 6 The lady and my brother mooped / Oh yes. They are going to moop
## 7 The girl is lorping the lady
## 8 The girl and the lady are lorping
## 9 Suzy lorped the cat.
## 10 Suzy and the cat lorped.
## 11 Find BB gorping CM!
## 12 The girl is pilking the boy
## 13 The girl and the boy are pilking!
## 14 The boy and the girl are pilking!
## 15 The girl is pilking the boy
## 16 The girl and the boy are pilking!
## 17 The girl is pilking the boy
## 18 The girl and the boy are pilking!
## 19 The boy and the girl are pilking!
## 20 They boy is going to moop the lady
## 21 They boy is going to moop the lady
## 22 He's kradding him!
## 23 He's kradding!
## 24 He's kradding him!
## 25 He's kradding!
## 26 He's kradding him!
## 27 He's kradding!
## 28 The cat lorped the bunny!
## 29 The cat lorped!
## 30 She is pilking!
## 31 she is pilking?
## 32 she is pilking?
## 33 she is pilking?
## 34 Oh Look! The duck is gorping the bunny!
## 35 Oh Look! The duck and bunny are zubbing!
## 36 And Bill was blicking the duck.
## 37 And Bill was blicking.
## 38 Oh Look! The duck is gorping the bunny!
## 39 Oh Look! The duck is gorping the bunny!
## 40 Look! The duck is gorping the bunny!
## 41 Look! The duck and the bunny are gorping!
## 42 the duck is gorping the frog
## 43 the duck and the frog are gorping
## 44 the duck is gorping the bunny!
## 45 <NA>
## 46 Jane is gonna meek!
## 47 Hey...Jim is gonna blick the cat!
## 48 Hey...Jim is gonna blick!
## 49 Hey...Jim is gonna blick the cat!
## 50 Hey...Jim is gonna blick!
## 51 He's gorping him!
## 52 He's gorping!
## 53 He's gorping him!
## 54 He's gorping!
## 55 He's gorping him!
## 56 He's gorping!
## 57 He's gorping him!
## 58 He's gorping!
## 59 He's gorping him!
## 60 He's gorping!
## test_question
## 1 Look, wow! Where's mooping?Do you see mooping? Find mooping!
## 2 Look, wow! Where's mooping?Do you see mooping? Find mooping!
## 3 Look, wow! Where's lorping? Find lorping!
## 4 Look, wow! Where's lorping? Find lorping!
## 5 Look, wow! Where's mooping?Do you see mooping? Find mooping!
## 6 Look, wow! Where's mooping?Do you see mooping? Find mooping!
## 7 Do you see lorping?
## 8 Do you see lorping?
## 9 Do you see lorping?
## 10 Do you see lorping?
## 11 Find BB gorping CM!
## 12 <NA>
## 13 <NA>
## 14 <NA>
## 15 <NA>
## 16 <NA>
## 17 <NA>
## 18 <NA>
## 19 <NA>
## 20 Look! Where's mooping? Do you see mooping? Find mooping
## 21 Look! Where's mooping? Do you see mooping? Find mooping
## 22 Find kradding!
## 23 Find kradding!
## 24 Find kradding!
## 25 Find kradding!
## 26 Find kradding!
## 27 Find kradding!
## 28 it's lorping it!
## 29 it's lorping!
## 30 Find pilking!
## 31 find pilking! where's pilking?
## 32 find pilking! where's pilking?
## 33 find pilking! where's pilking?
## 34 Find gorping
## 35 Find zubbing!
## 36 Find X-ing!
## 37 Find X-ing!
## 38 Find gorping
## 39 Find gorping
## 40 Where's the gorping now?
## 41 Where's the gorping now?
## 42 Oh! They're different now!Where's gorping now? Find gorping!
## 43 Oh! They're different now!Where's gorping now? Find gorping!
## 44 They're different now! Where is gorping now?Find gorping!
## 45 Where's meeking? Find meeking
## 46 Where's meeking? Find meeking
## 47 Find blicking! Where’s blicking? See? Where’s blicking?
## 48 Find blicking! Where’s blicking? See? Where’s blicking?
## 49 Find blicking! Where’s blicking? See? Where’s blicking?
## 50 Find blicking! Where’s blicking? See? Where’s blicking?
## 51 Find gorping.
## 52 Find gorping.
## 53 Find gorping.
## 54 Find gorping.
## 55 Find gorping.
## 56 Find gorping.
## 57 Find gorping.
## 58 Find gorping.
## 59 Find gorping.
## 60 Find gorping.
## inclusion_certainty
## 1 2
## 2 2
## 3 2
## 4 2
## 5 2
## 6 2
## 7 NA
## 8 NA
## 9 NA
## 10 NA
## 11 2
## 12 2
## 13 1
## 14 1
## 15 1
## 16 1
## 17 2
## 18 1
## 19 1
## 20 2
## 21 2
## 22 2
## 23 2
## 24 2
## 25 2
## 26 2
## 27 2
## 28 2
## 29 2
## 30 2
## 31 NA
## 32 2
## 33 2
## 34 2
## 35 2
## 36 2
## 37 2
## 38 1
## 39 1
## 40 2
## 41 2
## 42 2
## 43 2
## 44 2
## 45 1
## 46 1
## 47 2
## 48 2
## 49 2
## 50 2
## 51 2
## 52 2
## 53 2
## 54 2
## 55 2
## 56 2
## 57 2
## 58 2
## 59 2
## 60 2
## note
## 1 <NA>
## 2 <NA>
## 3 <NA>
## 4 <NA>
## 5 imputed from arunachalam2010
## 6 imputed from arunachalam2010
## 7 <NA>
## 8 <NA>
## 9 <NA>
## 10 <NA>
## 11 imputed from Naigles1996
## 12 <NA>
## 13 intransitive is 2 nouns, and difficulty depends on videos in scene
## 14 <NA>
## 15 <NA>
## 16 intransitive is 2 nouns, and difficulty depends on videos in scene
## 17 <NA>
## 18 intransitive is 2 nouns, and difficulty depends on videos in scene
## 19 intransitive is 2 nouns, and difficulty depends on videos in scene
## 20 <NA>
## 21 <NA>
## 22 <NA>
## 23 <NA>
## 24 <NA>
## 25 <NA>
## 26 <NA>
## 27 <NA>
## 28 <NA>
## 29 <NA>
## 30 <NA>
## 31 <NA>
## 32 <NA>
## 33 <NA>
## 34 <NA>
## 35 <NA>
## 36 <NA>
## 37 <NA>
## 38 data quite noisey: collapse across two type of testing procedures: one tested four novel verb in transitive, the other tested two novel verb in transitive and than in inintransitive
## 39 data quite noisey: collapse across two type of testing procedures: one tested four novel verb in transitive, the other tested two novel verb in transitive and than in inintransitive
## 40 <NA>
## 41 <NA>
## 42 calculated SD from raw
## 43 calculated SD from raw
## 44 <NA>
## 45 online study
## 46 online study
## 47 <NA>
## 48 <NA>
## 49 <NA>
## 50 this paper also has a condition that kiddos tested on the second day
## 51 <NA>
## 52 <NA>
## 53 <NA>
## 54 <NA>
## 55 <NA>
## 56 <NA>
## 57 <NA>
## 58 <NA>
## 59 <NA>
## 60 <NA>
## n_1 x_1 x_2 x_2_raw sd_1 sd_2 sd_2_raw t d
## 1 20 0.6700000 0.5 NA NA NA NA 3.19 0.71
## 2 20 0.5700000 0.5 NA NA NA NA 1.34 NA
## 3 20 0.5900000 0.5 NA 0.20000000 0.20000000 NA NA NA
## 4 20 0.5600000 0.5 NA 0.23000000 0.23000000 NA NA NA
## 5 20 0.5700000 0.5 0.4100000 0.20000000 0.20000000 NA NA NA
## 6 20 0.5900000 0.5 0.6000000 0.23000000 0.23000000 NA NA NA
## 7 19 0.4700000 0.5 0.4600000 0.16000000 0.16000000 NA NA NA
## 8 19 0.3400000 0.5 0.4300000 0.18000000 0.18000000 NA NA NA
## 9 19 0.3700000 0.5 0.4200000 0.15000000 0.15000000 NA NA NA
## 10 19 0.3500000 0.5 0.4200000 0.17000000 0.17000000 NA NA NA
## 11 20 0.5535714 0.5 NA 0.13653846 0.13653846 NA NA NA
## 12 8 0.6000000 0.5 NA 0.16970563 0.16970563 NA NA NA
## 13 8 0.3819444 0.5 NA 0.16970563 0.16970563 NA NA NA
## 14 8 0.5652778 0.5 NA 0.16970563 0.16970563 NA NA NA
## 15 6 0.5600000 0.5 NA 0.14696938 0.14696938 NA NA NA
## 16 6 0.6500000 0.5 NA 0.14696938 0.14696938 NA NA NA
## 17 8 0.5638889 0.5 NA 0.16970563 0.16970563 NA NA NA
## 18 8 0.3708333 0.5 NA 0.16970563 0.16970563 NA NA NA
## 19 8 0.5777778 0.5 NA 0.16970563 0.16970563 NA NA NA
## 20 21 0.4300000 0.5 NA 0.13000000 0.13000000 NA NA NA
## 21 21 0.4100000 0.5 NA 0.17000000 0.17000000 NA NA NA
## 22 12 0.5600000 0.5 NA 0.16000000 0.16000000 NA NA NA
## 23 12 0.6000000 0.5 NA 0.16000000 0.16000000 NA NA NA
## 24 12 0.6200000 0.5 NA 0.10000000 0.10000000 NA NA NA
## 25 12 0.4900000 0.5 NA 0.11000000 0.11000000 NA NA NA
## 26 12 0.5800000 0.5 NA 0.18000000 0.18000000 NA NA NA
## 27 12 0.6300000 0.5 NA 0.19000000 0.19000000 NA NA NA
## 28 16 0.5600000 0.5 NA 0.09000000 0.09000000 NA NA NA
## 29 16 0.5300000 0.5 NA 0.14000000 0.14000000 NA NA NA
## 30 16 0.4900000 0.5 NA 0.12000000 0.12000000 NA NA NA
## 31 24 0.5294118 0.5 NA 0.18181818 0.18181818 NA NA NA
## 32 16 0.5500000 0.5 NA 0.18000000 0.18000000 NA NA NA
## 33 15 0.4900000 0.5 NA 0.14000000 0.14000000 NA NA NA
## 34 17 0.5300000 0.5 0.4200000 0.16710000 0.16710000 0.1456000 NA NA
## 35 17 0.5654658 0.5 0.5095031 0.16486769 0.16486769 0.2045463 NA NA
## 36 8 0.6797804 0.5 NA 0.20000000 0.20000000 NA NA NA
## 37 8 0.6200000 0.5 NA 0.20000000 0.20000000 NA NA NA
## 38 33 0.5400000 0.5 0.4586000 0.08040000 0.08040000 NA NA NA
## 39 34 0.5565000 0.5 0.4793000 0.10010000 0.10010000 NA NA NA
## 40 12 0.5480769 0.5 NA 0.13653846 0.13653846 NA NA NA
## 41 12 0.5951036 0.5 NA 0.10546139 0.10546139 NA NA NA
## 42 20 0.5051546 0.5 NA 0.12164948 0.12164948 NA NA NA
## 43 16 0.5647558 0.5 NA 0.11889597 0.11889597 NA NA NA
## 44 18 0.4900000 0.5 0.4900000 0.42426407 0.42426407 0.1552000 1.72 0.41
## 45 16 0.4262877 0.5 NA 0.12670219 0.12670219 NA NA NA
## 46 17 0.5331492 0.5 NA 0.16629834 0.16629834 NA NA NA
## 47 8 0.6267880 0.5 NA 0.16000000 0.05591678 NA NA NA
## 48 8 0.5530201 0.5 NA 0.15000000 0.05369128 NA NA NA
## 49 8 0.7035111 0.5 NA 0.14000000 0.04941482 NA NA NA
## 50 8 0.4291667 0.5 NA 0.07463905 0.07463905 NA NA NA
## 51 8 0.6700000 0.5 NA 0.13000000 0.13000000 NA NA NA
## 52 8 0.5500000 0.5 NA 0.21000000 0.21000000 NA NA NA
## 53 8 0.7000000 0.5 NA 0.16000000 0.16000000 NA NA NA
## 54 8 0.5100000 0.5 NA 0.13000000 0.13000000 NA NA NA
## 55 8 0.6600000 0.5 NA 0.18000000 0.18000000 NA NA NA
## 56 8 0.5300000 0.5 NA 0.17000000 0.17000000 NA NA NA
## 57 12 0.6700000 0.5 NA 0.06000000 0.06000000 NA NA NA
## 58 12 0.4700000 0.5 NA 0.20000000 0.20000000 NA NA NA
## 59 12 0.5700000 0.5 NA 0.17000000 0.17000000 NA NA NA
## 60 12 0.6400000 0.5 NA 0.09000000 0.09000000 NA NA NA
## d_calc d_var_calc es_method unique_infant test_method
## 1 0.71330568 0.06272013 t_one unique_condition point
## 2 0.29963311 0.05224450 t_one unique_condition point
## 3 0.45000000 0.05506250 group_means_one unique_condition look
## 4 0.26086957 0.05170132 group_means_one unique_condition look
## 5 0.35000000 0.05306250 group_means_one unique_condition look
## 6 0.39130435 0.05382798 group_means_one unique_condition look
## 7 -0.18750000 0.05355674 group_means_one unique_condition look
## 8 -0.88888889 0.07342430 group_means_one unique_condition look
## 9 -0.86666667 0.07239766 group_means_one unique_condition look
## 10 -0.88235294 0.07311965 group_means_one unique_condition look
## 11 0.39235412 0.05384854 group_means_one unique_condition look
## 12 0.58925565 0.14670139 group_means_one unique_condition look
## 13 -0.69564903 0.15524547 group_means_one unique_condition look
## 14 0.38465299 0.13424737 group_means_one unique_condition look
## 15 0.40824829 0.18055556 group_means_one unique_condition look
## 16 1.02062073 0.25347222 group_means_one unique_condition look
## 17 0.37646889 0.13385805 group_means_one unique_condition look
## 18 -0.76112188 0.16120666 group_means_one unique_condition look
## 19 0.45830995 0.13812800 group_means_one unique_condition look
## 20 -0.53846154 0.05452240 group_means_one unique_condition look
## 21 -0.52941176 0.05429231 group_means_one unique_condition look
## 22 0.37500000 0.08919271 group_means_one unique_condition look
## 23 0.62500000 0.09960937 group_means_one unique_condition look
## 24 1.20000000 0.14333333 group_means_one unique_condition look
## 25 -0.09090909 0.08367769 group_means_one unique_condition look
## 26 0.44444444 0.09156379 group_means_one unique_condition look
## 27 0.68421053 0.10283934 group_means_one unique_condition look
## 28 0.66666667 0.07638889 group_means_one unique_condition look
## 29 0.21428571 0.06393495 group_means_one unique_condition look
## 30 -0.08333333 0.06271701 group_means_one unique_condition look
## 31 0.16176471 0.04221183 group_means_one unique_condition look
## 32 0.27777778 0.06491127 group_means_one unique_condition look
## 33 -0.07142857 0.06683673 group_means_one unique_condition look
## 34 0.17953321 0.05977153 group_means_one not_unique look
## 35 0.39708108 0.06346098 group_means_one not_unique look
## 36 0.89890210 0.17550156 group_means_one unique_condition look
## 37 0.60000000 0.14750000 group_means_one unique_condition look
## 38 0.49751244 0.03405331 group_means_one not_unique look
## 39 0.56443556 0.03409688 group_means_one not_unique look
## 40 0.35211268 0.08849931 group_means_one unique_condition look
## 41 0.90178571 0.11721739 group_means_one unique_condition look
## 42 0.04237288 0.05004489 group_means_one unique_condition look
## 43 0.54464286 0.07176987 group_means_one unique_condition look
## 44 -0.02357023 0.05557099 group_means_one not_unique look
## 45 -0.58177570 0.07307697 group_means_one unique_condition look
## 46 0.19933555 0.05999220 group_means_one unique_condition look
## 47 0.79242523 0.16424611 group_means_one unique_condition look
## 48 0.35346756 0.13280871 group_means_one unique_condition look
## 49 1.45365038 0.25706871 group_means_one unique_condition look
## 50 -0.94901173 0.18128895 group_means_one unique_condition look
## 51 1.30769231 0.23187870 group_means_one unique_condition look
## 52 0.23809524 0.12854308 group_means_one unique_condition look
## 53 1.25000000 0.22265625 group_means_one unique_condition look
## 54 0.07692308 0.12536982 group_means_one unique_condition look
## 55 0.88888889 0.17438272 group_means_one unique_condition look
## 56 0.17647059 0.12694637 group_means_one unique_condition look
## 57 2.83333333 0.41782407 group_means_one unique_condition look
## 58 -0.15000000 0.08427083 group_means_one unique_condition look
## 59 0.41176471 0.09039792 group_means_one unique_condition look
## 60 1.55555556 0.18415638 group_means_one unique_condition look
## agent_argument_number visual_stimuli_pair
## 1 varying direct_caused_action_parallel_actions
## 2 varying direct_caused_action_parallel_actions
## 3 1 direct_caused_action_parallel_actions
## 4 2 direct_caused_action_parallel_actions
## 5 varying direct_caused_action_parallel_actions
## 6 varying direct_caused_action_parallel_actions
## 7 1 direct_caused_action_parallel_actions
## 8 2 direct_caused_action_parallel_actions
## 9 1 direct_caused_action_parallel_actions
## 10 1 direct_caused_action_parallel_actions
## 11 1 direct_caused_action_parallel_actions
## 12 1 indirect_caused_action_parallel_actions
## 13 2 indirect_caused_action_parallel_actions
## 14 2 indirect_caused_action_parallel_actions
## 15 1 indirect_caused_action_parallel_actions
## 16 2 indirect_caused_action_parallel_actions
## 17 1 indirect_caused_action_parallel_actions
## 18 2 indirect_caused_action_parallel_actions
## 19 2 indirect_caused_action_parallel_actions
## 20 1 direct_caused_action_parallel_actions
## 21 1 direct_caused_action_parallel_actions
## 22 varying direct_caused_action_one_action
## 23 varying direct_caused_action_one_action
## 24 varying direct_caused_action_one_action
## 25 varying direct_caused_action_one_action
## 26 varying direct_caused_action_parallel_actions
## 27 varying direct_caused_action_parallel_actions
## 28 varying direct_caused_action_parallel_actions
## 29 varying direct_caused_action_parallel_actions
## 30 varying indirect_caused_action_parallel_actions
## 31 varying direct_caused_action_parallel_actions
## 32 varying direct_caused_action_parallel_actions
## 33 varying direct_caused_action_parallel_actions
## 34 1 direct_caused_action_parallel_actions
## 35 2 direct_caused_action_parallel_actions
## 36 varying direct_caused_action_parallel_actions
## 37 varying direct_caused_action_parallel_actions
## 38 1 direct_caused_action_parallel_actions
## 39 1 direct_caused_action_parallel_actions
## 40 1 direct_caused_action_parallel_actions
## 41 2 direct_caused_action_parallel_actions
## 42 1 indirect_caused_action_parallel_actions
## 43 2 indirect_caused_action_parallel_actions
## 44 1 direct_caused_action_parallel_actions
## 45 1 direct_caused_action_one_action
## 46 1 direct_caused_action_one_action
## 47 varying direct_caused_action_one_action
## 48 varying direct_caused_action_one_action
## 49 varying direct_caused_action_one_action
## 50 varying direct_caused_action_one_action
## 51 1 direct_caused_action_one_action
## 52 1 direct_caused_action_one_action
## 53 1 indirect_caused_action_one_action
## 54 1 indirect_caused_action_one_action
## 55 1 indirect_caused_action_parallel_actions
## 56 1 indirect_caused_action_parallel_actions
## 57 varying direct_caused_action_one_action
## 58 varying direct_caused_action_one_action
## 59 varying indirect_caused_action_parallel_actions
## 60 varying indirect_caused_action_parallel_actions
## adult_participant data_source_clean publication_year row_id
## 1 no text/table 2010 1
## 2 no text/table 2010 2
## 3 no text/table 2013 3
## 4 no text/table 2013 4
## 5 no imputed 2013 5
## 6 no imputed 2013 6
## 7 no author_contact 2019 7
## 8 no author_contact 2019 8
## 9 no author_contact 2019 9
## 10 no author_contact 2019 10
## 11 no imputed NA 11
## 12 no plot 2012 12
## 13 no plot 2012 13
## 14 no plot 2012 14
## 15 no text/table 2012 15
## 16 no text/table 2012 16
## 17 no plot 2012 17
## 18 no plot 2012 18
## 19 no plot 2012 19
## 20 no text/table 2020 20
## 21 no text/table 2020 21
## 22 no text/table 2015 22
## 23 no text/table 2015 23
## 24 no text/table 2015 24
## 25 no text/table 2015 25
## 26 no text/table 2015 26
## 27 no text/table 2015 27
## 28 no text/table 2015 28
## 29 no text/table 2015 29
## 30 no text/table 2015 30
## 31 no text/table 2015 31
## 32 no text/table 2015 32
## 33 no text/table 2015 33
## 34 no plot NA 34
## 35 no plot NA 35
## 36 no plot 2014 36
## 37 no plot 2014 37
## 38 no author_contact 5 38
## 39 no author_contact 6 39
## 40 no author_contact 1990 40
## 41 no author_contact 1990 41
## 42 no text/table 1993 42
## 43 no text/table 1993 43
## 44 no text/table 2011 44
## 45 no author_contact 2017 45
## 46 no author_contact 2017 46
## 47 no text/table 2009 47
## 48 no text/table 2009 48
## 49 no text/table 2009 49
## 50 no text/table 2009 50
## 51 no text/table 2012 51
## 52 no text/table 2012 52
## 53 no text/table 2012 53
## 54 no text/table 2012 54
## 55 no text/table 2012 55
## 56 no text/table 2012 56
## 57 no text/table 2012 57
## 58 no text/table 2012 58
## 59 no text/table 2012 59
## 60 no text/table 2012 60