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  "Type": "Package",
  "Title": "An Automatic Suite for Estimation of Various Effect Size\nMeasures",
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  "Authors@R": "c(\nperson(given = c(\"Corentin\", \"J.\"), family= \"Gosling\",  role = c(\"aut\", \"cre\"),\nemail = \"corentin.gosling@parisnanterre.fr\"),\nperson(given = \"Samuele\",\nfamily= \"Cortese\", role = \"aut\",\nemail = \"samuele.cortese@gmail.com\"),\nperson(given = \"Marco\",\nfamily= \"Solmi\", role = \"aut\",\nemail = \"marco.solmi83@gmail.com\"),\nperson(given = \"Belen\",\nfamily= \"Haza\", role = \"aut\",\nemail = \"hazabelen@gmail.com\"),\nperson(given = \"Eduard\",\nfamily= \"Vieta\", role = \"aut\",\nemail = \"EVIETA@clinic.cat\"),\nperson(given = \"Richard\",\nfamily= \"Delorme\", role = \"aut\",\nemail = \"richard.delorme.rdb@gmail.com\"),\nperson(given = \"Paolo\",\nfamily= \"Fusar-Poli\",  role = \"aut\",\nemail = \"Paolo.fusar-poli@kcl.ac.uk\"),\nperson(given = \"Joaquim\",\nfamily= \"Radua\",  role = \"aut\",\nemail = \"radua@clinic.cat\"))",
  "Maintainer": "Corentin J. Gosling <corentin.gosling@parisnanterre.fr>",
  "Description": "Automatically estimate 11 effect size measures from a\nwell-formatted dataset. Various other functions can help, for\nexample, removing dependency between several effect sizes, or\nidentifying differences between two datasets. This package is\nmainly designed to assist in conducting a systematic review\nwith a meta-analysis but can be useful to any researcher\ninterested in estimating an effect size.",
  "License": "GPL (>= 3)",
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  "Packaged": {
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    "User": "root"
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  "Author": "Corentin J. Gosling [aut, cre], Samuele Cortese [aut], Marco\nSolmi [aut], Belen Haza [aut], Eduard Vieta [aut], Richard\nDelorme [aut], Paolo Fusar-Poli [aut], Joaquim Radua [aut]",
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  "Repository": "https://corentinjgosling.r-universe.dev",
  "Date/Publication": "2025-04-11 20:34:05 UTC",
  "RemoteUrl": "https://github.com/cran/metaConvert",
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  "_created": "2026-05-26T08:40:43.000Z",
  "_published": "2026-05-26T08:45:26.859Z",
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    "compare_df",
    "convert_df",
    "data_extraction_sheet",
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    "es_from_2x2_prop",
    "es_from_2x2_sum",
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    "es_from_ancova_f_pval",
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    "es_from_ancova_md_pval",
    "es_from_ancova_md_sd",
    "es_from_ancova_md_se",
    "es_from_ancova_means_ci",
    "es_from_ancova_means_sd",
    "es_from_ancova_means_sd_pooled_adj",
    "es_from_ancova_means_sd_pooled_crude",
    "es_from_ancova_means_se",
    "es_from_ancova_t",
    "es_from_ancova_t_pval",
    "es_from_anova_f",
    "es_from_anova_pval",
    "es_from_beta_std",
    "es_from_beta_unstd",
    "es_from_cases_time",
    "es_from_chisq",
    "es_from_chisq_pval",
    "es_from_cohen_d",
    "es_from_cohen_d_adj",
    "es_from_etasq",
    "es_from_etasq_adj",
    "es_from_fisher_z",
    "es_from_hedges_g",
    "es_from_md_ci",
    "es_from_md_pval",
    "es_from_md_sd",
    "es_from_md_se",
    "es_from_mean_change_ci",
    "es_from_mean_change_pval",
    "es_from_mean_change_sd",
    "es_from_mean_change_se",
    "es_from_means_ci",
    "es_from_means_ci_pre_post",
    "es_from_means_sd",
    "es_from_means_sd_pooled",
    "es_from_means_sd_pre_post",
    "es_from_means_se",
    "es_from_means_se_pre_post",
    "es_from_med_min_max",
    "es_from_med_min_max_quarts",
    "es_from_med_quarts",
    "es_from_or",
    "es_from_or_ci",
    "es_from_or_pval",
    "es_from_or_se",
    "es_from_paired_f",
    "es_from_paired_f_pval",
    "es_from_paired_t",
    "es_from_paired_t_pval",
    "es_from_pearson_r",
    "es_from_phi",
    "es_from_plot_ancova_means",
    "es_from_plot_means",
    "es_from_pt_bis_r",
    "es_from_pt_bis_r_pval",
    "es_from_rr_ci",
    "es_from_rr_pval",
    "es_from_rr_se",
    "es_from_student_t",
    "es_from_student_t_pval",
    "es_from_user_adj",
    "es_from_user_crude",
    "es_variab_from_means_ci",
    "es_variab_from_means_sd",
    "es_variab_from_means_se",
    "see_input_data",
    "summary.metaConvert"
  ],
  "_datasets": [
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      "name": "df.compare1",
      "title": "Fictitious dataset 1",
      "object": "df.compare1",
      "class": [
        "data.frame"
      ],
      "fields": [
        "study_id",
        "author",
        "year",
        "n_exp",
        "n_nexp",
        "prop_cases_exp",
        "prop_cases_nexp"
      ],
      "rows": 5,
      "table": true,
      "tojson": true
    },
    {
      "name": "df.compare2",
      "title": "Fictitious dataset 2",
      "object": "df.compare2",
      "class": [
        "data.frame"
      ],
      "fields": [
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        "author",
        "year",
        "n_exp",
        "n_nexp",
        "prop_cases_exp",
        "prop_cases_nexp"
      ],
      "rows": 6,
      "table": true,
      "tojson": true
    },
    {
      "name": "df.haza",
      "title": "Meta-analytic dataset inspired from Haza and colleagues (2024)",
      "object": "df.haza",
      "class": [
        "data.frame"
      ],
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        "year",
        "study_id",
        "type_publication",
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        "outcome",
        "n_exp",
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        "mean_exp",
        "mean_sd_exp",
        "mean_se_exp",
        "mean_nexp",
        "mean_sd_nexp",
        "mean_se_nexp",
        "mean_ci_lo_exp",
        "mean_ci_up_exp",
        "mean_ci_lo_nexp",
        "mean_ci_up_nexp",
        "md",
        "md_se",
        "student_t_pval",
        "cohen_d",
        "etasq",
        "etasq_partial",
        "cohen_d_adj",
        "etasq_adj",
        "n_cov_etasq",
        "cov_outcome_etasq",
        "n_cov_ancova",
        "cov_outcome_r",
        "ancova_mean_exp",
        "ancova_mean_sd_exp",
        "ancova_mean_se_exp",
        "ancova_mean_nexp",
        "ancova_mean_sd_nexp",
        "ancova_mean_se_nexp",
        "ancova_mean_ci_lo_exp",
        "ancova_mean_ci_up_exp",
        "ancova_mean_ci_lo_nexp",
        "ancova_mean_ci_up_nexp",
        "ancova_f",
        "n_cases",
        "n_controls",
        "n_sample",
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        "anova_f",
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        "chisq",
        "plot_mean_exp",
        "plot_mean_sd_lo_exp",
        "plot_mean_sd_up_exp",
        "plot_mean_se_lo_exp",
        "plot_mean_se_up_exp",
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        "plot_mean_ci_up_exp",
        "plot_mean_nexp",
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        "plot_mean_se_lo_nexp",
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        "plot_ancova_mean_sd_up_exp",
        "plot_ancova_mean_se_lo_exp",
        "plot_ancova_mean_se_up_exp",
        "plot_ancova_mean_ci_lo_exp",
        "plot_ancova_mean_ci_up_exp",
        "plot_ancova_mean_nexp",
        "plot_ancova_mean_sd_lo_nexp",
        "plot_ancova_mean_sd_up_nexp",
        "plot_ancova_mean_se_lo_nexp",
        "plot_ancova_mean_se_up_nexp",
        "plot_ancova_mean_ci_lo_nexp",
        "plot_ancova_mean_ci_up_nexp",
        "reverse_means",
        "reverse_ancova_means",
        "reverse_plot_means",
        "reverse_plot_ancova_means",
        "reverse_ancova_f",
        "reverse_med",
        "reverse_d",
        "reverse_etasq",
        "reverse_student_t",
        "reverse_anova_f",
        "reverse_chisq",
        "reverse_2x2",
        "reverse_prop",
        "dup"
      ],
      "rows": 170,
      "table": true,
      "tojson": true
    },
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      "title": "Short version of the df.haza dataset",
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      "class": [
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        "tbl_df",
        "tbl",
        "data.frame"
      ],
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        "mean_se_nexp",
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        "mean_ci_up_exp",
        "mean_ci_lo_nexp",
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        "md",
        "md_se",
        "student_t_pval",
        "cohen_d",
        "etasq",
        "etasq_partial",
        "cohen_d_adj",
        "etasq_adj",
        "n_cov_etasq",
        "cov_outcome_etasq",
        "n_cov_ancova",
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        "ancova_mean_se_exp",
        "ancova_mean_nexp",
        "ancova_mean_sd_nexp",
        "ancova_mean_se_nexp",
        "ancova_mean_ci_lo_exp",
        "ancova_mean_ci_up_exp",
        "ancova_mean_ci_lo_nexp",
        "ancova_mean_ci_up_nexp",
        "ancova_f",
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        "n_sample",
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        "prop_cases_nexp",
        "n_cases_exp",
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        "q3_exp",
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        "plot_mean_sd_up_exp",
        "plot_mean_se_lo_exp",
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        "plot_mean_ci_lo_exp",
        "plot_mean_ci_up_exp",
        "plot_mean_nexp",
        "plot_mean_sd_lo_nexp",
        "plot_mean_sd_up_nexp",
        "plot_mean_se_lo_nexp",
        "plot_mean_se_up_nexp",
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        "plot_mean_ci_up_nexp",
        "plot_ancova_mean_exp",
        "plot_ancova_mean_sd_lo_exp",
        "plot_ancova_mean_sd_up_exp",
        "plot_ancova_mean_se_lo_exp",
        "plot_ancova_mean_se_up_exp",
        "plot_ancova_mean_ci_lo_exp",
        "plot_ancova_mean_ci_up_exp",
        "plot_ancova_mean_nexp",
        "plot_ancova_mean_sd_lo_nexp",
        "plot_ancova_mean_sd_up_nexp",
        "plot_ancova_mean_se_lo_nexp",
        "plot_ancova_mean_se_up_nexp",
        "plot_ancova_mean_ci_lo_nexp",
        "plot_ancova_mean_ci_up_nexp",
        "reverse_means",
        "reverse_ancova_means",
        "reverse_plot_means",
        "reverse_plot_ancova_means",
        "reverse_ancova_f",
        "reverse_med",
        "reverse_d",
        "reverse_etasq",
        "reverse_student_t",
        "reverse_anova_f",
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        "info_measure_adjusted",
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      "rows": 37,
      "table": true,
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    }
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  "_help": [
    {
      "page": "metaConvert-package",
      "title": "metaConvert: An R Package Dedicated to Automated Effect Size Calculations",
      "topics": [
        "metaConvert-package"
      ]
    },
    {
      "page": "aggregate_df",
      "title": "Aggregate a dataframe containing dependent effect sizes",
      "topics": [
        "aggregate_df"
      ]
    },
    {
      "page": "compare_df",
      "title": "Flag the differences between two dataframes.",
      "topics": [
        "compare_df"
      ]
    },
    {
      "page": "convert_df",
      "title": "Automatically compute effect sizes from a well formatted dataset",
      "topics": [
        "convert_df"
      ]
    },
    {
      "page": "data_extraction_sheet",
      "title": "Data extraction sheet generator",
      "topics": [
        "data_extraction_sheet"
      ]
    },
    {
      "page": "df.compare1",
      "title": "Fictitious dataset 1",
      "topics": [
        "df.compare1"
      ]
    },
    {
      "page": "df.compare2",
      "title": "Fictitious dataset 2",
      "topics": [
        "df.compare2"
      ]
    },
    {
      "page": "df.haza",
      "title": "Meta-analytic dataset inspired from Haza and colleagues (2024)",
      "topics": [
        "df.haza"
      ]
    },
    {
      "page": "df.short",
      "title": "Short version of the df.haza dataset",
      "topics": [
        "df.short"
      ]
    },
    {
      "page": "es_from_2x2",
      "title": "Convert a 2x2 table into several effect size measures",
      "topics": [
        "es_from_2x2"
      ]
    },
    {
      "page": "es_from_2x2_prop",
      "title": "Convert the proportion of occurrence of a binary event in two independent groups into several effect size measures",
      "topics": [
        "es_from_2x2_prop"
      ]
    },
    {
      "page": "es_from_2x2_sum",
      "title": "Convert a table with the number of cases and row marginal sums into several effect size measures",
      "topics": [
        "es_from_2x2_sum"
      ]
    },
    {
      "page": "es_from_ancova_f",
      "title": "Convert a F-statistic obtained from an ANCOVA model into several effect size measures.",
      "topics": [
        "es_from_ancova_f"
      ]
    },
    {
      "page": "es_from_ancova_f_pval",
      "title": "Convert a two-tailed p-value of an ANCOVA t-test into several effect size measures.",
      "topics": [
        "es_from_ancova_f_pval"
      ]
    },
    {
      "page": "es_from_ancova_md_ci",
      "title": "Convert an adjusted mean difference and adjusted standard deviation between two independent groups obtained from an ANCOVA model into several effect size measures",
      "topics": [
        "es_from_ancova_md_ci"
      ]
    },
    {
      "page": "es_from_ancova_md_pval",
      "title": "Convert an adjusted mean difference and adjusted standard deviation between two independent groups obtained from an ANCOVA model into several effect size measures",
      "topics": [
        "es_from_ancova_md_pval"
      ]
    },
    {
      "page": "es_from_ancova_md_sd",
      "title": "Convert an adjusted mean difference and adjusted standard deviation between two independent groups obtained from an ANCOVA model into several effect size measures",
      "topics": [
        "es_from_ancova_md_sd"
      ]
    },
    {
      "page": "es_from_ancova_md_se",
      "title": "Convert an adjusted mean difference and standard error between two independent groups obtained from an ANCOVA model into several effect size measures",
      "topics": [
        "es_from_ancova_md_se"
      ]
    },
    {
      "page": "es_from_ancova_means_ci",
      "title": "Convert means and 95% CIs of two independent groups obtained from an ANCOVA model into several effect size measures",
      "topics": [
        "es_from_ancova_means_ci"
      ]
    },
    {
      "page": "es_from_ancova_means_sd",
      "title": "Convert means and standard deviations of two independent groups obtained from an ANCOVA model into several effect size measures",
      "topics": [
        "es_from_ancova_means_sd"
      ]
    },
    {
      "page": "es_from_ancova_means_sd_pooled_adj",
      "title": "Convert means and adjusted pooled standard deviation of two independent groups obtained from an ANCOVA model into several effect size measures",
      "topics": [
        "es_from_ancova_means_sd_pooled_adj"
      ]
    },
    {
      "page": "es_from_ancova_means_sd_pooled_crude",
      "title": "Convert adjusted means obtained from an ANCOVA model and crude pooled standard deviation of two independent groups into several effect size measures",
      "topics": [
        "es_from_ancova_means_sd_pooled_crude"
      ]
    },
    {
      "page": "es_from_ancova_means_se",
      "title": "Convert means and standard errors of two independent groups obtained from an ANCOVA model into several effect size measures",
      "topics": [
        "es_from_ancova_means_se"
      ]
    },
    {
      "page": "es_from_ancova_t",
      "title": "Convert a t-statistic obtained from an ANCOVA model into several effect size measures.",
      "topics": [
        "es_from_ancova_t"
      ]
    },
    {
      "page": "es_from_ancova_t_pval",
      "title": "Convert a two-tailed p-value of an ANCOVA t-test into several effect size measures.",
      "topics": [
        "es_from_ancova_t_pval"
      ]
    },
    {
      "page": "es_from_anova_f",
      "title": "Convert a one-way independent ANOVA F-value to several effect size measures",
      "topics": [
        "es_from_anova_f"
      ]
    },
    {
      "page": "es_from_anova_pval",
      "title": "Convert a p-value from a one-way independent ANOVA to several effect size measures",
      "topics": [
        "es_from_anova_pval"
      ]
    },
    {
      "page": "es_from_beta_std",
      "title": "Convert a standardized regression coefficient and the standard deviation of the dependent variable into several effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_beta_unstd",
      "title": "Convert an unstandardized regression coefficient and the standard deviation of the dependent variable into several effect size measures",
      "topics": [
        "es_from_beta_unstd"
      ]
    },
    {
      "page": "es_from_cases_time",
      "title": "Convert the number of cases and the person-time of disease-free observation in two independent groups into an incidence rate ratio (IRR)",
      "topics": [
        "es_from_cases_time"
      ]
    },
    {
      "page": "es_from_chisq",
      "title": "Convert a chi-square value to several effect size measures",
      "topics": [
        "es_from_chisq"
      ]
    },
    {
      "page": "es_from_chisq_pval",
      "title": "Convert a p-value of a chi-square to several effect size measures",
      "topics": [
        "es_from_chisq_pval"
      ]
    },
    {
      "page": "es_from_cohen_d",
      "title": "Convert a Cohen's d value to several effect size measures",
      "topics": [
        "es_from_cohen_d"
      ]
    },
    {
      "page": "es_from_cohen_d_adj",
      "title": "Convert an adjusted Cohen's d value to several effect size measures",
      "topics": [
        "es_from_cohen_d_adj"
      ]
    },
    {
      "page": "es_from_etasq",
      "title": "Convert an eta-squared value to various effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_etasq_adj",
      "title": "Convert an adjusted eta-squared value (i.e., from an ANCOVA) to various effect size measures",
      "topics": [
        "es_from_etasq_adj"
      ]
    },
    {
      "page": "es_from_fisher_z",
      "title": "Convert a Fisher's z (r-to-z transformation) to several effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_hedges_g",
      "title": "Convert a Hedges' g value to other effect size measures (G, OR, COR)",
      "topics": [
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      ]
    },
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      "page": "es_from_md_ci",
      "title": "Convert a mean difference between two independent groups and 95% CI into several effect size measures",
      "topics": [
        "es_from_md_ci"
      ]
    },
    {
      "page": "es_from_md_pval",
      "title": "Convert a mean difference between two independent groups and its p-value into several effect size measures",
      "topics": [
        "es_from_md_pval"
      ]
    },
    {
      "page": "es_from_md_sd",
      "title": "Convert a mean difference between two independent groups and standard deviation into several effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_md_se",
      "title": "Convert a mean difference between two independent groups and its standard error into several effect size measures",
      "topics": [
        "es_from_md_se"
      ]
    },
    {
      "page": "es_from_mean_change_ci",
      "title": "Convert mean changes and standard deviations of two independent groups into standard effect size measures",
      "topics": [
        "es_from_mean_change_ci"
      ]
    },
    {
      "page": "es_from_mean_change_pval",
      "title": "Convert mean changes and standard deviations of two independent groups into standard effect size measures",
      "topics": [
        "es_from_mean_change_pval"
      ]
    },
    {
      "page": "es_from_mean_change_sd",
      "title": "Convert mean changes and standard deviations of two independent groups into standard effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_mean_change_se",
      "title": "Convert mean changes and standard errors of two independent groups into standard effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_means_ci",
      "title": "Convert means and 95% CI of two independent groups several effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_means_ci_pre_post",
      "title": "Convert pre-post means of two independent groups into various effect size measures",
      "topics": [
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      ]
    },
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      "page": "es_from_means_sd",
      "title": "Convert means and standard deviations of two independent groups into several effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_means_sd_pooled",
      "title": "Convert means of two groups and the pooled standard deviation into several effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_means_sd_pre_post",
      "title": "Convert pre-post means of two independent groups into various effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_means_se",
      "title": "Convert means and standard errors of two independent groups several effect size measures",
      "topics": [
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      ]
    },
    {
      "page": "es_from_means_se_pre_post",
      "title": "Convert pre-post means of two independent groups into various effect size measures",
      "topics": [
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      ]
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      "page": "es_from_med_min_max",
      "title": "Convert median, quartiles, and range of two independent groups into several effect size measures",
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    },
    {
      "page": "es_from_med_min_max_quarts",
      "title": "Convert median, range and interquartile range of two independent groups into several effect size measures",
      "topics": [
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      ]
    },
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      "page": "es_from_med_quarts",
      "title": "Convert median and interquartile range of two independent groups into several effect size measures",
      "topics": [
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      ]
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    {
      "page": "es_from_or",
      "title": "Convert an odds ratio value to several effect size measures",
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      "page": "es_from_or_ci",
      "title": "Convert an odds ratio value and its 95% confidence interval to several effect size measures",
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      "page": "es_from_or_pval",
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    {
      "page": "es_from_paired_f_pval",
      "title": "Convert two paired ANOVA f p-value of two independent groups into several effect size measures",
      "topics": [
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      "page": "es_from_paired_t",
      "title": "Convert two paired t-test value of two independent groups into several effect size measures",
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      "page": "es_from_paired_t_pval",
      "title": "Convert two paired t-test p-value obtained from two independent groups into several effect size measures",
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      "page": "es_from_pearson_r",
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      "title": "Converts the means and bounds of an error bar (generally extracted from a plot) into four effect measures (SMD, MD, OR, COR)",
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      "title": "Convert means and/or standard deviations of two independent groups into two effect measures (VR/CVR)",
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