stop_if_missing <- function(x, name) {
if (is.na(x)) stop(sprintf("Missing required input: %s", name), call. = FALSE)
}
# Exact small-sample correction factor used by metafor (.cmicalc).
hedges_correction <- function(df) {
ifelse(df <= 1, NA_real_, exp(lgamma(df/2) - log(sqrt(df/2)) - lgamma((df - 1)/2)))
}
pooled_sd <- function(n_high, n_low, sd_high, sd_low) {
sqrt(((n_high - 1) * sd_high^2 + (n_low - 1) * sd_low^2) / (n_high + n_low - 2))
}
d_from_groups_independent <- function(n_high, n_low, mean_high, mean_low, sd_high, sd_low) {
s <- pooled_sd(n_high, n_low, sd_high, sd_low)
(mean_low - mean_high) / s
}
var_d_independent <- function(d, n_high, n_low) {
n <- n_high + n_low
(n / (n_high * n_low)) + (d^2 / (2 * (n - 2)))
}
compute_effect_size <- function(
paper_key,
study_id,
effect_id,
method_used,
sign_convention = "d = mean(low) - mean(high)",
n_high = NA_integer_,
n_low = NA_integer_,
mean_high = NA_real_,
mean_low = NA_real_,
sd_high = NA_real_,
sd_low = NA_real_,
notes_on_assumptions = "",
imputed_flag = FALSE,
needs_sensitivity = TRUE
) {
d <- NA_real_
v <- NA_real_
g <- NA_real_
v_g <- NA_real_
computed_from_suggested <- NA_character_
design_used <- if (startsWith(method_used, "between_")) "Between-Subjects" else NA_character_
if (method_used == "between_groups") {
computed_from_suggested <- "groups"
stop_if_missing(n_high, "n_high")
stop_if_missing(n_low, "n_low")
stop_if_missing(mean_high, "mean_high")
stop_if_missing(mean_low, "mean_low")
stop_if_missing(sd_high, "sd_high")
stop_if_missing(sd_low, "sd_low")
d <- d_from_groups_independent(n_high, n_low, mean_high, mean_low, sd_high, sd_low)
v <- var_d_independent(d, n_high, n_low)
df_used <- n_high + n_low - 2
J <- hedges_correction(df_used)
g <- J * d
v_g <- (J^2) * v
} else {
stop(sprintf("Unknown method_used: %s", method_used), call. = FALSE)
}
inputs_used <- paste(
c(
sprintf("method=%s", method_used),
sprintf("sign_convention=%s", sign_convention),
sprintf("n_low=%s", n_low),
sprintf("n_high=%s", n_high),
sprintf("mean_low=%s", mean_low),
sprintf("mean_high=%s", mean_high),
sprintf("sd_low=%s", sd_low),
sprintf("sd_high=%s", sd_high)
),
collapse = ", "
)
audit <- data.frame(
paper_key = paper_key,
study_id = study_id,
effect_id = effect_id,
design = design_used,
method_used = method_used,
computed_from_suggested = computed_from_suggested,
inputs_used = inputs_used,
d = d,
v = v,
g = g,
v_g = v_g,
notes_on_assumptions = notes_on_assumptions,
imputed_flag = imputed_flag,
needs_sensitivity = needs_sensitivity
)
yaml_snippet <- sprintf(
"effect_size:\\n metric: SMD\\n d: %.12f\\n v: %.12f\\n computed_from: %s\\n needs_review: false\\n notes: \"%s\"\\n",
d, v, computed_from_suggested, gsub(pattern = "\"", replacement = "'", x = inputs_used)
)
list(audit = audit, yaml_snippet = yaml_snippet)
}Effect size computation: feltzzarpentine2010knowmattersless
Study 1 (Experiment 1): Stanley bank cases
Effect s1_e1: High Stakes vs Low Stakes
paper_key <- "feltzzarpentine2010knowmattersless"
study_id <- 1
effect_id <- "s1_e1"
inputs <- list(
n_high = 39L,
n_low = 34L,
mean_high = 4.26,
mean_low = 3.68,
sd_high = 2.14,
sd_low = 1.91
)
inputs$n_high
[1] 39
$n_low
[1] 34
$mean_high
[1] 4.26
$mean_low
[1] 3.68
$sd_high
[1] 2.14
$sd_low
[1] 1.91# Original scale: 1 = Strongly Agree ... 7 = Strongly Disagree.
# Reverse-score so higher values indicate stronger agreement (match other extractions).
inputs$mean_high <- 8 - inputs$mean_high
inputs$mean_low <- 8 - inputs$mean_low
inputs$n_high
[1] 39
$n_low
[1] 34
$mean_high
[1] 3.74
$mean_low
[1] 4.32
$sd_high
[1] 2.14
$sd_low
[1] 1.91res_s1_e1 <- compute_effect_size(
paper_key = paper_key,
study_id = study_id,
effect_id = effect_id,
method_used = "between_groups",
n_high = inputs$n_high,
n_low = inputs$n_low,
mean_high = inputs$mean_high,
mean_low = inputs$mean_low,
sd_high = inputs$sd_high,
sd_low = inputs$sd_low,
notes_on_assumptions = "Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Group Ns inferred from total N=152 + reported independent-samples t-test dfs in Notes [6]-[8] (PDF p.17); means/SD from Notes [6]."
)
res_s1_e1$audit paper_key study_id effect_id design
1 feltzzarpentine2010knowmattersless 1 s1_e1 Between-Subjects
method_used computed_from_suggested
1 between_groups groups
inputs_used
1 method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=34, n_high=39, mean_low=4.32, mean_high=3.74, sd_low=1.91, sd_high=2.14
d v g v_g
1 0.2848258 0.0556241 0.2818047 0.05445035
notes_on_assumptions
1 Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Group Ns inferred from total N=152 + reported independent-samples t-test dfs in Notes [6]-[8] (PDF p.17); means/SD from Notes [6].
imputed_flag needs_sensitivity
1 FALSE TRUEcat(res_s1_e1$yaml_snippet)effect_size:\n metric: SMD\n d: 0.284825809531\n v: 0.055624098388\n computed_from: groups\n needs_review: false\n notes: "method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=34, n_high=39, mean_low=4.32, mean_high=3.74, sd_low=1.91, sd_high=2.14"\nEffect s1_e2: Ignorant High Stakes vs Low Stakes
paper_key <- "feltzzarpentine2010knowmattersless"
study_id <- 1
effect_id <- "s1_e2"
inputs <- list(
n_high = 39L,
n_low = 34L,
mean_high = 3.59,
mean_low = 3.68,
sd_high = 1.90,
sd_low = 1.91
)
inputs$n_high
[1] 39
$n_low
[1] 34
$mean_high
[1] 3.59
$mean_low
[1] 3.68
$sd_high
[1] 1.9
$sd_low
[1] 1.91# Original scale: 1 = Strongly Agree ... 7 = Strongly Disagree.
# Reverse-score so higher values indicate stronger agreement (match other extractions).
inputs$mean_high <- 8 - inputs$mean_high
inputs$mean_low <- 8 - inputs$mean_low
inputs$n_high
[1] 39
$n_low
[1] 34
$mean_high
[1] 4.41
$mean_low
[1] 4.32
$sd_high
[1] 1.9
$sd_low
[1] 1.91res_s1_e2 <- compute_effect_size(
paper_key = paper_key,
study_id = study_id,
effect_id = effect_id,
method_used = "between_groups",
n_high = inputs$n_high,
n_low = inputs$n_low,
mean_high = inputs$mean_high,
mean_low = inputs$mean_low,
sd_high = inputs$sd_high,
sd_low = inputs$sd_low,
notes_on_assumptions = "Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Group Ns inferred from total N=152 + reported independent-samples t-test dfs in Notes [6]-[8] (PDF p.17); means/SD from Notes [6]-[7]."
)
res_s1_e2$audit paper_key study_id effect_id design
1 feltzzarpentine2010knowmattersless 1 s1_e2 Between-Subjects
method_used computed_from_suggested
1 between_groups groups
inputs_used
1 method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=34, n_high=39, mean_low=4.32, mean_high=4.41, sd_low=1.91, sd_high=1.9
d v g v_g
1 -0.04725267 0.05506851 -0.04675146 0.05390649
notes_on_assumptions
1 Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Group Ns inferred from total N=152 + reported independent-samples t-test dfs in Notes [6]-[8] (PDF p.17); means/SD from Notes [6]-[7].
imputed_flag needs_sensitivity
1 FALSE TRUEcat(res_s1_e2$yaml_snippet)effect_size:\n metric: SMD\n d: -0.047252666502\n v: 0.055068514393\n computed_from: groups\n needs_review: false\n notes: "method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=34, n_high=39, mean_low=4.32, mean_high=4.41, sd_low=1.91, sd_high=1.9"\nEffect s1_e3: Low Attributer–High Subject Stakes vs Low Stakes
paper_key <- "feltzzarpentine2010knowmattersless"
study_id <- 1
effect_id <- "s1_e3"
inputs <- list(
n_high = 40L,
n_low = 34L,
mean_high = 4.75,
mean_low = 3.68,
sd_high = 1.89,
sd_low = 1.91
)
inputs$n_high
[1] 40
$n_low
[1] 34
$mean_high
[1] 4.75
$mean_low
[1] 3.68
$sd_high
[1] 1.89
$sd_low
[1] 1.91# Original scale: 1 = Strongly Agree ... 7 = Strongly Disagree.
# Reverse-score so higher values indicate stronger agreement (match other extractions).
inputs$mean_high <- 8 - inputs$mean_high
inputs$mean_low <- 8 - inputs$mean_low
inputs$n_high
[1] 40
$n_low
[1] 34
$mean_high
[1] 3.25
$mean_low
[1] 4.32
$sd_high
[1] 1.89
$sd_low
[1] 1.91res_s1_e3 <- compute_effect_size(
paper_key = paper_key,
study_id = study_id,
effect_id = effect_id,
method_used = "between_groups",
n_high = inputs$n_high,
n_low = inputs$n_low,
mean_high = inputs$mean_high,
mean_low = inputs$mean_low,
sd_high = inputs$sd_high,
sd_low = inputs$sd_low,
notes_on_assumptions = "Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Group Ns inferred from total N=152 + reported independent-samples t-test dfs in Notes [6]-[8] (PDF p.17); means/SD from Notes [6] and [8]."
)
res_s1_e3$audit paper_key study_id effect_id design
1 feltzzarpentine2010knowmattersless 1 s1_e3 Between-Subjects
method_used computed_from_suggested
1 between_groups groups
inputs_used
1 method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=34, n_high=40, mean_low=4.32, mean_high=3.25, sd_low=1.91, sd_high=1.89
d v g v_g
1 0.5633972 0.05661605 0.5575046 0.05543794
notes_on_assumptions
1 Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Group Ns inferred from total N=152 + reported independent-samples t-test dfs in Notes [6]-[8] (PDF p.17); means/SD from Notes [6] and [8].
imputed_flag needs_sensitivity
1 FALSE TRUEcat(res_s1_e3$yaml_snippet)effect_size:\n metric: SMD\n d: 0.563397246349\n v: 0.056616045659\n computed_from: groups\n needs_review: false\n notes: "method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=34, n_high=40, mean_low=4.32, mean_high=3.25, sd_low=1.91, sd_high=1.89"\nStudy 2 (Experiment 2): Minimal bridge cases
Effect s2_e1: Minimal High Stakes vs Minimal Low Stakes
paper_key <- "feltzzarpentine2010knowmattersless"
study_id <- 2
effect_id <- "s2_e1"
inputs <- list(
n_high = 39L,
n_low = 41L,
mean_high = 3.23,
mean_low = 3.29,
sd_high = 1.58,
sd_low = 1.76
)
inputs$n_high
[1] 39
$n_low
[1] 41
$mean_high
[1] 3.23
$mean_low
[1] 3.29
$sd_high
[1] 1.58
$sd_low
[1] 1.76# Original scale: 1 = Strongly Agree ... 7 = Strongly Disagree.
# Reverse-score so higher values indicate stronger agreement (match other extractions).
inputs$mean_high <- 8 - inputs$mean_high
inputs$mean_low <- 8 - inputs$mean_low
inputs$n_high
[1] 39
$n_low
[1] 41
$mean_high
[1] 4.77
$mean_low
[1] 4.71
$sd_high
[1] 1.58
$sd_low
[1] 1.76res_s2_e1 <- compute_effect_size(
paper_key = paper_key,
study_id = study_id,
effect_id = effect_id,
method_used = "between_groups",
n_high = inputs$n_high,
n_low = inputs$n_low,
mean_high = inputs$mean_high,
mean_low = inputs$mean_low,
sd_high = inputs$sd_high,
sd_low = inputs$sd_low,
notes_on_assumptions = "Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Group Ns inferred from total N=119 + reported independent-samples t-test dfs in Notes [10]-[11] (PDF p.17); means/SD from Notes [10]."
)
res_s2_e1$audit paper_key study_id effect_id design
1 feltzzarpentine2010knowmattersless 2 s2_e1 Between-Subjects
method_used computed_from_suggested
1 between_groups groups
inputs_used
1 method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=41, n_high=39, mean_low=4.71, mean_high=4.77, sd_low=1.76, sd_high=1.58
d v g v_g
1 -0.03582675 0.0500395 -0.03548097 0.04907825
notes_on_assumptions
1 Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Group Ns inferred from total N=119 + reported independent-samples t-test dfs in Notes [10]-[11] (PDF p.17); means/SD from Notes [10].
imputed_flag needs_sensitivity
1 FALSE TRUEcat(res_s2_e1$yaml_snippet)effect_size:\n metric: SMD\n d: -0.035826752835\n v: 0.050039497468\n computed_from: groups\n needs_review: false\n notes: "method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=41, n_high=39, mean_low=4.71, mean_high=4.77, sd_low=1.76, sd_high=1.58"\nEffect s2_e2: Minimal High Stakes vs Attributer
paper_key <- "feltzzarpentine2010knowmattersless"
study_id <- 2
effect_id <- "s2_e2"
inputs <- list(
n_high = 39L,
n_low = 39L,
mean_high = 3.23,
mean_low = 3.87,
sd_high = 1.58,
sd_low = 1.13
)
inputs$n_high
[1] 39
$n_low
[1] 39
$mean_high
[1] 3.23
$mean_low
[1] 3.87
$sd_high
[1] 1.58
$sd_low
[1] 1.13# Original scale: 1 = Strongly Agree ... 7 = Strongly Disagree.
# Reverse-score so higher values indicate stronger agreement (match other extractions).
inputs$mean_high <- 8 - inputs$mean_high
inputs$mean_low <- 8 - inputs$mean_low
inputs$n_high
[1] 39
$n_low
[1] 39
$mean_high
[1] 4.77
$mean_low
[1] 4.13
$sd_high
[1] 1.58
$sd_low
[1] 1.13res_s2_e2 <- compute_effect_size(
paper_key = paper_key,
study_id = study_id,
effect_id = effect_id,
method_used = "between_groups",
n_high = inputs$n_high,
n_low = inputs$n_low,
mean_high = inputs$mean_high,
mean_low = inputs$mean_low,
sd_high = inputs$sd_high,
sd_low = inputs$sd_low,
notes_on_assumptions = "Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Group Ns inferred from total N=119 + reported independent-samples t-test dfs in Notes [10]-[11] (PDF p.17); means/SD from Notes [10] and [11]."
)
res_s2_e2$audit paper_key study_id effect_id design
1 feltzzarpentine2010knowmattersless 2 s2_e2 Between-Subjects
method_used computed_from_suggested
1 between_groups groups
inputs_used
1 method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=39, n_high=39, mean_low=4.13, mean_high=4.77, sd_low=1.13, sd_high=1.58
d v g v_g
1 -0.4659446 0.05271037 -0.4613288 0.0516712
notes_on_assumptions
1 Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Group Ns inferred from total N=119 + reported independent-samples t-test dfs in Notes [10]-[11] (PDF p.17); means/SD from Notes [10] and [11].
imputed_flag needs_sensitivity
1 FALSE TRUEcat(res_s2_e2$yaml_snippet)effect_size:\n metric: SMD\n d: -0.465944622655\n v: 0.052710369646\n computed_from: groups\n needs_review: false\n notes: "method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=39, n_high=39, mean_low=4.13, mean_high=4.77, sd_low=1.13, sd_high=1.58"\nStudy 3 (Experiment 3): Simplified bank cases
Effect s3_e1: Simplified High Stakes vs Simplified Low Stakes
paper_key <- "feltzzarpentine2010knowmattersless"
study_id <- 3
effect_id <- "s3_e1"
inputs <- list(
n_high = 42L,
n_low = 40L,
mean_high = 3.83,
mean_low = 3.85,
sd_high = 1.92,
sd_low = 1.73
)
inputs$n_high
[1] 42
$n_low
[1] 40
$mean_high
[1] 3.83
$mean_low
[1] 3.85
$sd_high
[1] 1.92
$sd_low
[1] 1.73# Original scale: 1 = Strongly Agree ... 7 = Strongly Disagree.
# Reverse-score so higher values indicate stronger agreement (match other extractions).
inputs$mean_high <- 8 - inputs$mean_high
inputs$mean_low <- 8 - inputs$mean_low
inputs$n_high
[1] 42
$n_low
[1] 40
$mean_high
[1] 4.17
$mean_low
[1] 4.15
$sd_high
[1] 1.92
$sd_low
[1] 1.73res_s3_e1 <- compute_effect_size(
paper_key = paper_key,
study_id = study_id,
effect_id = effect_id,
method_used = "between_groups",
n_high = inputs$n_high,
n_low = inputs$n_low,
mean_high = inputs$mean_high,
mean_low = inputs$mean_low,
sd_high = inputs$sd_high,
sd_low = inputs$sd_low,
notes_on_assumptions = "Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Means/SD and t(df) from Notes [14] (PDF p.18). Group Ns inferred from Notes [14] and cross-comparison dfs in Notes [14] and [16] (PDF p.18)."
)
res_s3_e1$audit paper_key study_id effect_id design
1 feltzzarpentine2010knowmattersless 3 s3_e1 Between-Subjects
method_used computed_from_suggested
1 between_groups groups
inputs_used
1 method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=40, n_high=42, mean_low=4.15, mean_high=4.17, sd_low=1.73, sd_high=1.92
d v g v_g
1 -0.01092991 0.04881027 -0.01082707 0.04789605
notes_on_assumptions
1 Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Means/SD and t(df) from Notes [14] (PDF p.18). Group Ns inferred from Notes [14] and cross-comparison dfs in Notes [14] and [16] (PDF p.18).
imputed_flag needs_sensitivity
1 FALSE TRUEcat(res_s3_e1$yaml_snippet)effect_size:\n metric: SMD\n d: -0.010929910312\n v: 0.048810270453\n computed_from: groups\n needs_review: false\n notes: "method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=40, n_high=42, mean_low=4.15, mean_high=4.17, sd_low=1.73, sd_high=1.92"\nStudy 4 (Experiment 4): High vs low stakes bridge (trucks)
Effect s4_e1: High Stakes Bridge vs Low Stakes Bridge
paper_key <- "feltzzarpentine2010knowmattersless"
study_id <- 4
effect_id <- "s4_e1"
inputs <- list(
n_high = 70L,
n_low = 70L,
mean_high = 3.83,
mean_low = 3.40,
sd_high = 1.96,
sd_low = 1.74
)
inputs$n_high
[1] 70
$n_low
[1] 70
$mean_high
[1] 3.83
$mean_low
[1] 3.4
$sd_high
[1] 1.96
$sd_low
[1] 1.74# Original scale: 1 = Strongly Agree ... 7 = Strongly Disagree.
# Reverse-score so higher values indicate stronger agreement (match other extractions).
inputs$mean_high <- 8 - inputs$mean_high
inputs$mean_low <- 8 - inputs$mean_low
inputs$n_high
[1] 70
$n_low
[1] 70
$mean_high
[1] 4.17
$mean_low
[1] 4.6
$sd_high
[1] 1.96
$sd_low
[1] 1.74res_s4_e1 <- compute_effect_size(
paper_key = paper_key,
study_id = study_id,
effect_id = effect_id,
method_used = "between_groups",
n_high = inputs$n_high,
n_low = inputs$n_low,
mean_high = inputs$mean_high,
mean_low = inputs$mean_low,
sd_high = inputs$sd_high,
sd_low = inputs$sd_low,
notes_on_assumptions = "Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Total N=140 from Experiment 4 text (PDF p.12); means/SD and t(df) from Notes [16] (PDF p.18). Group Ns inferred from Notes [16] cross-comparison dfs (PDF p.18)."
)
res_s4_e1$audit paper_key study_id effect_id design
1 feltzzarpentine2010knowmattersless 4 s4_e1 Between-Subjects
method_used computed_from_suggested
1 between_groups groups
inputs_used
1 method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=70, n_high=70, mean_low=4.6, mean_high=4.17, sd_low=1.74, sd_high=1.96
d v g v_g
1 0.2320226 0.02876648 0.230759 0.02845399
notes_on_assumptions
1 Means reverse-scored as (8 - M) because response scale is 1=Strongly Agree ... 7=Strongly Disagree (to align with other extractions where higher=more agreement). Total N=140 from Experiment 4 text (PDF p.12); means/SD and t(df) from Notes [16] (PDF p.18). Group Ns inferred from Notes [16] cross-comparison dfs (PDF p.18).
imputed_flag needs_sensitivity
1 FALSE TRUEcat(res_s4_e1$yaml_snippet)effect_size:\n metric: SMD\n d: 0.232022644708\n v: 0.028766481135\n computed_from: groups\n needs_review: false\n notes: "method=between_groups, sign_convention=d = mean(low) - mean(high), n_low=70, n_high=70, mean_low=4.6, mean_high=4.17, sd_low=1.74, sd_high=1.96"\n