Estimation Statistics with Confidence Intervals
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Documentation for package ‘esci’ version 1.0.3
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-- C --
| 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 |
-- D --
| 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) |
-- E --
| esci_plot_difference_axis_x | Add a difference axis to the x axis of an esci forest plot |
| 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 |
| 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) |
| 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 |
-- G --
| geom_meta_diamond_h | Meta-analysis diamond |
-- J --
| 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 |
-- M --
| 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. |
-- O --
| overview | Calculates descriptive statistics for a continuous variable |
| overview_nominal | Calculates descriptive statistics for a numerical variable |
-- P --
| 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 |
| print.esci_estimate | Print an esci_estimate |
-- T --
| 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 |