Function reference • esci

Estimates for continuous outcomes

estimate_magnitude(): Estimates for a continuous variable with no grouping (single-group design)

estimate_mdiff_2x2_between(): Estimates for a 2x2 between-subjects design with a continuous outcome variable

estimate_mdiff_2x2_mixed(): Estimates for a 2x2 mixed factorial design with a continuous outcome variable

estimate_mdiff_ind_contrast(): Estimates for a multi-group design with a continuous outcome variable

estimate_mdiff_one(): Estimates for a single-group design with a continuous outcome variable compared to a reference or population value

estimate_mdiff_paired(): Estimates for a repeated-measures study with two measures of a continuous variable

estimate_mdiff_two(): Estimates for a two-group study with a continuous outcome variable

Estimates for categorical outcomes

estimate_pdiff_ind_contrast(): Estimates for a multi-group study with a categorical outcome variable

estimate_pdiff_one(): Estimates for a single-group design with a categorical outcome variable compared to a reference or population value.

estimate_pdiff_paired(): Estimates for a repeated-measures study with two measures of a categorical variable

estimate_pdiff_two(): Estimates for a two-group study with a categorical outcome variable

estimate_proportion(): Estimates for a categorical variable with no grouping (single-group design)

Estimates for Pearson’s r

estimate_r(): Estimates the linear correlation (Pearson's r) between two continuous variables

estimate_rdiff_two(): Estimates the difference in correlation for a design with two groups and two continuous outcome variables

Meta-analysis

meta_any(): Estimate any meta effect.

meta_d1(): Estimate a meta-analytic Cohen's d1 across multiple studies

meta_d2(): Estimate meta-analytic standardized mean difference across multiple two group studies (all paired, all independent, or a mix).

meta_mdiff_two(): Estimate meta-analytic difference in means across multiple two-group studies.

meta_mean(): Estimate a meta-analytic mean across multiple single-group studies.

meta_pdiff_two(): Estimate meta-analytic difference in proportions over multiple studies with two independent groups and a categorical outcome variable.

meta_proportion(): Estimate a meta-analytic proportion of outcomes over multiple studies with a categorical outcome variable.

meta_r(): Estimate meta-analytic Pearson's r across multiple studies with two continuous outcome variables.

Visualization

plot_correlation(): Plot an estimated Pearson's r value

plot_describe(): Plot a histogram or dotplot of an estimated magnitude with raw data

plot_interaction(): Plot the interaction from a 2x2 design

plot_magnitude(): Plot the mean or median for a continuous variable

plot_mdiff(): Plots for comparing continuous outcome variables between conditions

plot_meta(): Generates a forest plot displaying results of a meta-analysis

plot_pdiff(): Plots for comparing categorical outcome variables between conditions

plot_proportion(): Plot an estimated proportion

plot_rdiff(): Plots for comparing Pearson r values between conditions

plot_scatter(): Generates a scatter plot of data for two continuous variables

Hypothesis testing

test_correlation(): Test a hypothesis about the strength of a Pearson's r correlation

test_mdiff(): Test a hypothesis about a difference in a continuous outcome variable.

test_pdiff(): Test a hypothesis about a difference in proportion

test_rdiff(): Test a hypothesis about a difference in correlation strength

Sample data sets

data_altruism_happiness: Altruism Happiness - Ch12 - from Brethel-Haurwitz and Marsh (2014)

data_anchor_estimate_ma: Anchor Estimate ma - Ch9 - Many Labs replications of Jacowitz and Kahneman (1995)

data_basol_badnews: Basol badnews - Ch07 - from Basol et al. (2020)

data_bem_psychic: Bem Psychic - Ch13 - from Bem and Honorton (1994)

data_bodywellf: BodyWellF - Ch12 - Body Satisfaction and Well-being data for females from Figure 11.24 right panel

data_bodywellfm: BodyWellFM - Ch12 - Body Satisfaction and Well-being data from Figure 11.1

data_bodywellm: BodyWellM - Ch12 - Body Satisfaction and Well-being data for males from Figure 11.24 left panel

data_campus_involvement: Campus Involvement - Ch11 - for End-of-Chapter Exercise 11.7

data_chap_8_paired_ex_8.18: Fictitious data from an unrealistically small HEAT study comparing scores for a single group of students before and after a workshop on climate change.

data_clean_moral: Clean moral - Ch07 - from Schnall et al. (2008), Study 1, and Johnson et al. (2014)

data_college_survey_1: College survey 1 - Ch03 - for End-of-Chapter Exercise 3.3

data_college_survey_2: College survey 2 - Ch05 - for End-of-Chapter Exercise 5.4

data_damischrcj: DamischRCJ - Ch9 - from 6 Damisch studies, and Calin-Jageman and Caldwell (2014)

data_effronraj_fakenews: EffronRaj fakenews - Ch8 - from Effron and Raj (2020)

data_emotion_heartrate: Emotion heartrate - Ch8 - from Lakens (2013)

data_exam_scores: Exam Scores - Ch11 - for End-of-Chapter Exercise 11.2

data_flag_priming_ma: Flag Priming ma - Ch9 - Many Labs replications of Carter et al. (2011)

data_gender_math_iat: Gender math IAT - Ch07 - Ithaca and SDSU replications of Nosek et al. (2002)

data_gender_math_iat_ma: Gender math IAT ma - Ch9 - Many Labs replications of Nosek et al. (2002)

data_halagappa: Halagappa - Ch14 - from Halagappa et al. (2007)

data_home_prices: Home Prices - Ch12 - for End-of-Chapter Exercise 12.2

data_kardas_expt_3: Kardas Expt 3 - Ch07 - from Kardas and O'Brien (2018), Experiment 3

data_kardas_expt_4: Kardas Expt 4 - Ch07 - from Kardas and O'Brien (2018), Experiment 4

data_labels_flavor: Labels flavor - Ch8 - from Floretta-Schiller et al. (2015)

data_latimier_3groups: Latimier 3Groups - Ch14 - 3 groups in Latimier et al. (2019)

data_latimier_prequiz: Latimier Prequiz - Ch03 - Prequiz group in Latimier et al. (2019)

data_latimier_quiz: Latimier Quiz - Ch03 - Quiz group in Latimier et al. (2019)

data_latimier_quiz_prequiz: Latimier Quiz Prequiz - Ch07 - Quiz and Prequiz groups in Latimier et al. (2019)

data_latimier_reread: Latimier Reread - Ch03 - Reread group in Latimier et al. (2019)

data_latimier_reread_prequiz: Latimier Reread Prequiz - Ch07 - Reread and Prequiz groups in Latimier et al. (2019)

data_latimier_reread_quiz: Latimier Reread Quiz - Ch07 - Reread and Quiz groups in Latimier et al. (2019)

data_macnamara_r_ma: Macnamara r ma - Ch11 - from Macnamara et al. (2014)

data_mccabemichael_brain: McCabeMichael brain - Ch9 - from Michael et al. (2013)

data_mccabemichael_brain2: McCabeMichael brain2 - Ch9 - from Michael et al. (2013)

data_meditationbrain: MeditationBrain - Ch15 - from Holzel et al. (2011)

data_organicmoral: OrganicMoral - Ch14 - from Eskine (2013)

data_penlaptop1: % transcription scores from pen and laptop group of Meuller et al., 2014

data_powerperformance_ma: PowerPerformance ma - Ch9 - from Burgmer and Englich (2012), and Cusack et al. (2015)

data_rattanmotivation: RattanMotivation - Ch14 - from Rattan et al. (2012)

data_religionsharing: ReligionSharing - Ch14 - for End-of-Chapter Exercise 14.3

data_religious_belief: Religious belief - Ch03 - for End-of-Chapter Exercise 3.5

data_selfexplain: SelfExplain - Ch15 - from McEldoon et al. (2013)

data_simmonscredibility: SimmonsCredibility - Ch14 - from Simmons and Nelson (2020)

data_sleep_beauty: Sleep Beauty - Ch11 - for End-of-Chapter Exercise 11.6

data_smithrecall: SmithRecall - Ch15 - from Smith et al. (2016)

data_stickgold: Stickgold - Ch06 - from Stickgold et al. (2000)

data_studystrategies: StudyStrategies - Ch14 - from O'Reilly et al. (1998)

data_thomason_1: Thomason 1 - Ch11 - from Thomason 1

data_videogameaggression: VideogameAggression - Ch15 - from Hilgard (2015)

Summarizing data

overview(): Calculates descriptive statistics for a continuous variable

overview_nominal(): Calculates descriptive statistics for a numerical variable

Confidence intervals in place of psychstat

CI_diamond_ratio(): Estimate the diamond ratio for a meta-analytic effect, a measure of heterogeneity

CI_smd_ind_contrast(): Estimate standardized mean difference (Cohen's d) for an independent groups contrast

CI_smd_one(): Estimate standardized mean difference (Cohen's d1) for a single group

Functions for jamovi

jamovicorrelation(): Correlations: Single Group

jamovidescribe(): Describe

jamovimagnitude(): Means and Medians: Single Group

jamovimdiff2x2(): Means and Medians: 2x2 Factorial

jamovimdiffindcontrast(): Means and Medians: Independent Groups Contrast

jamovimdiffpaired(): Means and Medians: Paired

jamovimdifftwo(): Means and Medians: Two Groups

jamovimetamdiff(): Meta-Analysis: Difference in Means

jamovimetamean(): Meta-Analysis: Means

jamovimetapdiff(): Meta-Analysis: Difference in Proportions

jamovimetaproportion(): Meta-Analysis: Proportions

jamovimetar(): Meta-Analysis: Correlations

jamovipdiffpaired(): Proportions: Paired

jamovipdifftwo(): Proportions: Two Groups

jamoviproportion(): Proportions: Single Group

jamovirdifftwo(): Correlations: Two Groups

Visualization helpers

geom_meta_diamond_h(): Meta-analysis diamond

esci_plot_difference_axis_x(): Add a difference axis to the x axis of an esci forest plot

Class esci-estimate

print(<esci_estimate>): Print an esci_estimate