partly addresses #21

API

@@ -1,23 +1,43 @@
-bf_contingency_tab(data, x, y = NULL, counts = NULL, ratio = NULL, sampling.plan = "indepMulti", fixed.margin = "rows", prior.concentration = 1, caption = NULL, output = "null", k = 2, ...)
-bf_corr_test(data, x, y, bf.prior = 0.707, caption = NULL, output = "null", k = 2, ...)
-bf_expr(bf.df, k = 2, output = "null", caption = NULL, ...)
-bf_extractor(bf.object, ...)
-bf_meta(data, d = prior, norm, c(mean = 0, sd = 0.3), tau = prior, invgamma, c(shape = 1, scale = 0.15), k = 2, output = "null", caption = NULL, messages = TRUE, ...)
-bf_oneway_anova(data, x, y, bf.prior = 0.707, caption = NULL, output = "null", paired = FALSE, k = 2, ...)
-bf_ttest(data, x, y = NULL, test.value = 0, paired = FALSE, bf.prior = 0.707, caption = NULL, output = "null", k = 2, ...)
-corr_objects(data, ci = FALSE, corr.method = "pearson", p.adjust.method = "none", beta = 0.1, k = 2, ...)
-expr_anova_bayes(data, x, y, paired = FALSE, bf.prior = 0.707, k = 2, ...)
-expr_anova_nonparametric(data, x, y, paired = FALSE, conf.type = "perc", conf.level = 0.95, k = 2, nboot = 100, stat.title = NULL, messages = TRUE, ...)
-expr_anova_parametric(data, x, y, paired = FALSE, effsize.type = "unbiased", partial = TRUE, conf.level = 0.95, nboot = 100, var.equal = FALSE, sphericity.correction = TRUE, k = 2, stat.title = NULL, messages = TRUE, ...)
-expr_anova_robust(data, x, y, paired = FALSE, tr = 0.1, nboot = 100, conf.level = 0.95, conf.type = "norm", k = 2, stat.title = NULL, messages = TRUE, ...)
-expr_contingency_tab(data, x, y = NULL, counts = NULL, ratio = NULL, nboot = 100, paired = FALSE, stat.title = NULL, legend.title = NULL, conf.level = 0.95, conf.type = "norm", bias.correct = TRUE, k = 2, messages = TRUE, ...)
-expr_corr_test(data, x, y, nboot = 100, beta = 0.1, type = "pearson", bf.prior = 0.707, conf.level = 0.95, conf.type = "norm", k = 2, stat.title = NULL, messages = TRUE, ...)
-expr_meta_bayes(data, d = prior, norm, c(mean = 0, sd = 0.3), tau = prior, invgamma, c(shape = 1, scale = 0.15), k = 2, messages = TRUE, ...)
-expr_meta_parametric(data, conf.level = 0.95, k = 2, messages = FALSE, output = "subtitle", caption = NULL, ...)
-expr_meta_robust(data, random = "mixture", k = 2, messages = FALSE, ...)
+# API for statsExpressions package
+
+## Exported functions
+
+expr_anova_bayes(data, x, y, paired = FALSE, bf.prior = 0.707, k = 2L, ...)
+expr_anova_nonparametric(data, x, y, paired = FALSE, conf.type = "perc", conf.level = 0.95, k = 2L, nboot = 100L, stat.title = NULL, ...)
+expr_anova_parametric(data, x, y, paired = FALSE, effsize.type = "unbiased", partial = TRUE, conf.level = 0.95, var.equal = FALSE, sphericity.correction = TRUE, k = 2L, stat.title = NULL, ...)
+expr_anova_robust(data, x, y, paired = FALSE, tr = 0.1, nboot = 100, conf.level = 0.95, k = 2L, stat.title = NULL, ...)
+expr_contingency_tab(data, x, y = NULL, counts = NULL, ratio = NULL, nboot = 100, paired = FALSE, stat.title = NULL, conf.level = 0.95, conf.type = "norm", bias.correct = TRUE, k = 2L, ...)
+expr_corr_test(data, x, y, beta = 0.1, type = "parametric", bf.prior = 0.707, conf.level = 0.95, k = 2L, stat.title = NULL, ...)
+expr_meta_bayes(data, d = prior("norm", c(mean = 0, sd = 0.3)), tau = prior("invgamma", c(shape = 1, scale = 0.15)), k = 2, messages = TRUE, ...)
+expr_meta_parametric(data, conf.level = 0.95, k = 2L, output = "subtitle", caption = NULL, messages = TRUE, ...)
+expr_meta_robust(data, random = "mixture", k = 2, messages = TRUE, ...)
+expr_onesample_proptest(data, x, y = NULL, counts = NULL, ratio = NULL, nboot = 100, paired = FALSE, stat.title = NULL, conf.level = 0.95, conf.type = "norm", bias.correct = TRUE, k = 2L, ...)
 expr_t_bayes(data, x, y, bf.prior = 0.707, paired = FALSE, k = 2, ...)
-expr_t_nonparametric(data, x, y, paired = FALSE, k = 2, conf.level = 0.95, conf.type = "norm", nboot = 100, stat.title = NULL, messages = TRUE, ...)
-expr_t_onesample(data, x, type = "parametric", test.value = 0, bf.prior = 0.707, robust.estimator = "onestep", effsize.type = "g", effsize.noncentral = TRUE, conf.level = 0.95, conf.type = "norm", nboot = 100, k = 2, stat.title = NULL, messages = TRUE, ...)
-expr_t_parametric(data, x, y, paired = FALSE, effsize.type = "g", effsize.noncentral = TRUE, conf.level = 0.95, var.equal = FALSE, k = 2, stat.title = NULL, ...)
-expr_t_robust(data, x, y, tr = 0.1, paired = FALSE, nboot = 100, conf.level = 0.95, conf.type = "norm", k = 2, stat.title = NULL, messages = TRUE, ...)
-expr_template(no.parameters, stat.title = NULL, statistic.text, stats.df, effsize.text, effsize.df, n, conf.level = 0.95, k = 2, k.parameter = 0, k.parameter2 = 0, n.text = NULL, ...)
+expr_t_nonparametric(data, x, y, paired = FALSE, k = 2L, conf.level = 0.95, conf.type = "norm", nboot = 100, stat.title = NULL, ...)
+expr_t_onesample(data, x, type = "parametric", test.value = 0, bf.prior = 0.707, robust.estimator = "onestep", effsize.type = "g", conf.level = 0.95, conf.type = "norm", nboot = 100, k = 2L, stat.title = NULL, ...)
+expr_t_parametric(data, x, y, paired = FALSE, effsize.type = "g", conf.level = 0.95, var.equal = FALSE, k = 2, stat.title = NULL, ...)
+expr_t_robust(data, x, y, tr = 0.1, paired = FALSE, conf.level = 0.95, nboot = 100, k = 2L, stat.title = NULL, ...)
+expr_template(no.parameters, stat.title = NULL, statistic.text, stats.df, effsize.text, effsize.df, n, conf.level = 0.95, k = 2L, k.parameter = 0L, k.parameter2 = 0L, n.text = NULL, ...)
+
+## Reexported objects
+
+::%$%
+zeallot::%<-%
+::%<>%
+::%>%
+rlang::%|%
+rlang::%||%
+rlang:::=
+tibble::as_tibble
+tidyBF::bf_contingency_tab
+tidyBF::bf_corr_test
+tidyBF::bf_meta
+tidyBF::bf_oneway_anova
+tidyBF::bf_ttest
+correlation::correlation
+ipmisc::long_to_wide_converter
+metaBMA::prior
+ipmisc::set_cwd
+ipmisc::signif_column
+ipmisc::specify_decimal_p
+tibble::tibble

DESCRIPTION

@@ -48,5 +48,6 @@ VignetteBuilder:
 Encoding: UTF-8
 Language: en-US
 LazyData: true
-Roxygen: list(markdown = TRUE)
+Roxygen: list(markdown = TRUE, roclets = c("rd", "namespace",
+    "collate", "pkgapi::api_roclet"))
 RoxygenNote: 7.1.1

NAMESPACE

@@ -13,6 +13,7 @@ export(bf_corr_test)
 export(bf_meta)
 export(bf_oneway_anova)
 export(bf_ttest)
+export(correlation)
 export(expr_anova_bayes)
 export(expr_anova_nonparametric)
 export(expr_anova_parametric)
@@ -43,7 +44,9 @@ importFrom(WRS2,yuen)
 importFrom(WRS2,yuen.effect.ci)
 importFrom(WRS2,yuend)
 importFrom(broomExtra,easystats_to_tidy_names)
+importFrom(broomExtra,glance_performance)
 importFrom(broomExtra,tidy)
+importFrom(broomExtra,tidy_parameters)
 importFrom(correlation,correlation)
 importFrom(dplyr,filter)
 importFrom(dplyr,inner_join)

R/helpers_meta_analysis_expressions.R

@@ -21,6 +21,7 @@
 #' @importFrom metafor rma
 #' @importFrom dplyr rename_all recode mutate
 #' @importFrom tidyBF meta_data_check
+#' @importFrom broomExtra tidy_parameters glance_performance
 #'
 #' @examples
 #' \donttest{
@@ -90,18 +91,8 @@ expr_meta_parametric <- function(data,
 
   # create a dataframe with coefficients
   df_tidy <-
-    coef(summary(meta_res)) %>%
-    as_tibble(.) %>%
-    dplyr::rename_all(
-      .tbl = .,
-      .funs = dplyr::recode,
-      se = "std.error",
-      zval = "statistic",
-      pval = "p.value",
-      ci.lb = "conf.low",
-      ci.ub = "conf.high"
-    ) %>%
-    dplyr::mutate(.data = ., term = "summary effect")
+    broomExtra::tidy_parameters(meta_res) %>%
+    dplyr::mutate(.data = ., term = "Overall")
 
   # preparing the subtitle
   subtitle <-
@@ -120,24 +111,8 @@ expr_meta_parametric <- function(data,
 
   #----------------------- model summary ------------------------------------
 
-  df_glance <-
-    with(
-      data = meta_res,
-      expr = tibble(
-        tau2 = tau2,
-        se.tau2 = se.tau2,
-        k = k,
-        p = p,
-        m = m,
-        QE = QE,
-        QEp = QEp,
-        QM = QM,
-        QMp = QMp,
-        I2 = I2,
-        H2 = H2,
-        int.only = int.only
-      )
-    )
+  # model summary
+  df_glance <- broomExtra::glance_performance(meta_res)
 
   # preparing the subtitle
   caption <-
@@ -166,11 +141,11 @@ expr_meta_parametric <- function(data,
       ),
       env = list(
         top.text = caption,
-        Q = specify_decimal_p(x = df_glance$QE, k = 0L),
-        df = specify_decimal_p(x = (df_glance$k - 1), k = 0L),
-        pvalue = specify_decimal_p(x = df_glance$QEp, k = k, p.value = TRUE),
-        tau2 = specify_decimal_p(x = df_glance$tau2, k = k),
-        I2 = paste(specify_decimal_p(x = df_glance$I2, k = 2L), "%", sep = "")
+        Q = specify_decimal_p(x = df_glance$cochran.qe, k = 0L),
+        df = specify_decimal_p(x = df_glance$df.residual, k = 0L),
+        pvalue = specify_decimal_p(x = df_glance$p.value.cochran.qe, k = k, p.value = TRUE),
+        tau2 = specify_decimal_p(x = df_glance$tau.squared, k = k),
+        I2 = paste(specify_decimal_p(x = df_glance$i.squared, k = 2L), "%", sep = "")
       )
     )
 

R/reexports.R

@@ -80,3 +80,9 @@ tidyBF::bf_oneway_anova
 #' @export
 #' @importFrom tidyBF prior
 tidyBF::prior
+
+# ----------------------- easystats -------------------------------------
+
+#' @export
+#' @importFrom correlation correlation
+correlation::correlation

codemeta.json

@@ -335,6 +335,6 @@
     "name": "Comprehensive R Archive Network (CRAN)",
     "url": "https://cran.r-project.org"
   },
-  "fileSize": "4282.836KB",
+  "fileSize": "4282.428KB",
   "readme": "https://github.com/IndrajeetPatil/statsExpressions/blob/master/README.md"
 }