cleanup code

R/infer-anova.R

@@ -40,16 +40,14 @@ infer_oneway_anova <- function(data, x, y, ...) UseMethod("infer_oneway_anova")
 
 #' @export
 infer_oneway_anova.default <- function(data, x, y, ...) {
+
   x1 <- enquo(x)
   y1 <- enquo(y)
 
-  fdata <-
-    data %>%
-    select(!! x1, !! y1)
-
-  sample_mean <- anova_avg(fdata, !! x1)
+  fdata        <- select(data, !! x1, !! y1)
+  sample_mean  <- anova_avg(fdata, !! x1)
   sample_stats <- anova_split(fdata, !! x1, !! y1, sample_mean)
-  k <- anova_calc(fdata, sample_stats, !! x1, !! y1)
+  k            <- anova_calc(fdata, sample_stats, !! x1, !! y1)
 
 
   result <- list(

R/infer-binom-test.R

@@ -82,11 +82,9 @@ print.infer_binom_calc <- function(x, ...) {
 #' @export
 #' @rdname infer_binom_calc
 infer_binom_test <- function(data, variable, prob = 0.5) {
+
   varyable <- enquo(variable)
-
-  fdata <-
-    data %>%
-    pull(!! varyable)
+  fdata    <- pull(data, !! varyable)
 
   if (!is.factor(fdata)) {
     stop("variable must be of type factor", call. = FALSE)

R/infer-chisq-assoc-test.R

@@ -41,16 +41,12 @@ infer_chisq_assoc_test <- function(data, x, y) UseMethod("infer_chisq_assoc_test
 
 #' @export
 infer_chisq_assoc_test.default <- function(data, x, y) {
+
   x1 <- enquo(x)
   y1 <- enquo(y)
 
-  xone <-
-    data %>%
-    pull(!! x1)
-
-  yone <-
-    data %>%
-    pull(!! y1)
+  xone <- pull(data, !! x1)
+  yone <- pull(data, !! y1)
 
   if (!is.factor(xone)) {
     stop("x must be a categorical variable")
@@ -61,7 +57,7 @@ infer_chisq_assoc_test.default <- function(data, x, y) {
   }
 
   # dimensions
-  k <- table(xone, yone)
+  k  <- table(xone, yone)
   dk <- dim(k)
   ds <- prod(dk)
   nr <- dk[1]
@@ -72,16 +68,16 @@ infer_chisq_assoc_test.default <- function(data, x, y) {
     twoway <- matrix(table(xone, yone), nrow = 2)
     df <- df_chi(twoway)
     ef <- efmat(twoway)
-    k <- pear_chsq(twoway, df, ef)
-    m <- lr_chsq(twoway, df, ef)
-    n <- yates_chsq(twoway)
-    p <- mh_chsq(twoway, n$total, n$prod_totals)
+    k  <- pear_chsq(twoway, df, ef)
+    m  <- lr_chsq(twoway, df, ef)
+    n  <- yates_chsq(twoway)
+    p  <- mh_chsq(twoway, n$total, n$prod_totals)
   } else {
     twoway <- matrix(table(xone, yone), nrow = dk[1])
     ef <- efm(twoway, dk)
     df <- df_chi(twoway)
-    k <- pear_chi(twoway, df, ef)
-    m <- lr_chsq2(twoway, df, ef, ds)
+    k  <- pear_chi(twoway, df, ef)
+    m  <- lr_chsq2(twoway, df, ef, ds)
   }
 
   j <- chigf(xone, yone, k$chi)

R/infer-chisq-gof-test.R

@@ -38,11 +38,9 @@ infer_chisq_gof_test <- function(data, x, y, correct = FALSE) UseMethod("infer_c
 
 #' @export
 infer_chisq_gof_test.default <- function(data, x, y, correct = FALSE) {
-  x1 <- enquo(x)
 
-  xcheck <-
-    data %>%
-    pull(!! x1)
+  x1 <- enquo(x)
+  xcheck <- pull(data, !! x1)
 
   xlen <-
     data %>%

R/infer-cochran-q-test.R

@@ -26,10 +26,10 @@ infer_cochran_qtest <- function(data, ...) UseMethod("infer_cochran_qtest")
 
 #' @export
 infer_cochran_qtest.default <- function(data, ...) {
+
   vars <- quos(...)
 
-  fdata <- data %>%
-    select(!!! vars)
+  fdata <- select(data, !!! vars)
 
   if (ncol(fdata) < 3) {
     stop("Please specify at least 3 variables.")

R/infer-levene-test.R

@@ -55,37 +55,29 @@ infer_levene_test <- function(data, ...) UseMethod("infer_levene_test")
 #' @rdname infer_levene_test
 infer_levene_test.default <- function(data, ..., group_var = NULL,
                                       trim_mean = 0.1) {
-  groupvar <- enquo(group_var)
-
+
+  groupvar  <- enquo(group_var)
   varyables <- quos(...)
-
-  fdata <-
-    data %>%
-    select(!!! varyables)
+  fdata     <- select(data, !!! varyables)
 
   if (quo_is_null(groupvar)) {
-    z <- as.list(fdata)
+    z  <- as.list(fdata)
     ln <- z %>% map_int(length)
     ly <- seq_len(length(z))
 
     if (length(z) < 2) {
       stop("Please specify at least two variables.", call. = FALSE)
     }
 
-    out <- gvar(ln, ly)
+    out   <- gvar(ln, ly)
     fdata <- unlist(z)
     groupvars <-
       out %>%
       unlist() %>%
       as.factor()
   } else {
-    fdata <-
-      fdata %>%
-      pull(1)
-
-    groupvars <-
-      data %>%
-      pull(!! groupvar)
+    fdata     <- pull(fdata, 1)
+    groupvars <- pull(data, !! groupvar)
 
     if (length(fdata) != length(groupvars)) {
       stop("Length of variable and group_var do not match.", call. = FALSE)

R/infer-mcnemar-test.R

@@ -55,6 +55,7 @@ infer_mcnemar_test <- function(data, x = NULL, y = NULL) UseMethod("infer_mcnema
 #' @export
 #'
 infer_mcnemar_test.default <- function(data, x = NULL, y = NULL) {
+
   if (is.matrix(data) | is.table(data)) {
     dat <- mcdata(data)
   } else {

R/infer-os-prop-test.R

@@ -46,29 +46,26 @@ infer_os_prop_test <- function(data, variable = NULL, prob = 0.5, phat = 0.5,
 infer_os_prop_test.default <- function(data, variable = NULL, prob = 0.5, phat = 0.5,
                                        alternative = c("both", "less", "greater", "all")) {
   if (is.numeric(data)) {
+
     method <- match.arg(alternative)
     k <- prop_comp(
       data, prob = prob, phat = phat,
       alternative = method
     )
-  } else {
-    varyables <- enquo(variable)
 
-    fdata <-
-      data %>%
-      pull(!! varyables)
+  } else {
 
-    n1 <- length(fdata)
+    varyables <- enquo(variable)
+    fdata     <- pull(data, !! varyables)
+    n1        <- length(fdata)
 
     n2 <-
       fdata %>%
       table() %>%
       `[[`(2)
 
-    phat <- round(n2 / n1, 4)
-
-    prob <- prob
-
+    phat   <- round(n2 / n1, 4)
+    prob   <- prob
     method <- match.arg(alternative)
 
     k <- prop_comp(

R/infer-os-t-test.R

@@ -57,11 +57,9 @@ infer_os_t_test <- function(data, x, mu = 0, alpha = 0.05,
 #'
 infer_os_t_test.default <- function(data, x, mu = 0, alpha = 0.05,
                                     alternative = c("both", "less", "greater", "all"), ...) {
-  x1 <- enquo(x)
-
-  xone <-
-    data %>%
-    pull(!! x1)
+
+  x1   <- enquo(x)
+  xone <- pull(data, !! x1)
 
   if (!is.numeric(xone)) {
     stop("x must be numeric")

R/infer-os-var-test.R

@@ -56,11 +56,9 @@ infer_os_var_test <- function(data, x, sd, confint = 0.95,
 #'
 infer_os_var_test.default <- function(data, x, sd, confint = 0.95,
                                       alternative = c("both", "less", "greater", "all"), ...) {
-  x1 <- enquo(x)
-
-  xone <-
-    data %>%
-    pull(!! x1)
+
+  x1   <- enquo(x)
+  xone <- pull(data, !! x1)
 
   if (!is.numeric(xone)) {
     stop("x must be numeric")

R/infer-runs-test.R

@@ -59,16 +59,10 @@ infer_runs_test <- function(data, x, drop = FALSE, split = FALSE, mean = FALSE,
 infer_runs_test.default <- function(data, x, drop = FALSE,
                                     split = FALSE, mean = FALSE,
                                     threshold = NA) {
-  x1 <- enquo(x)
-
-  xone <-
-    data %>%
-    pull(!! x1)
-
-  n <- length(xone)
-
-  # if (!(is.numeric(x) || is.integer(x)))
-  #     stop("x must be numeric or integer")
+
+  x1   <- enquo(x)
+  xone <- pull(data, !! x1)
+  n    <- length(xone)
 
   if (is.na(threshold)) {
     y <- unique(xone)
@@ -77,7 +71,6 @@ infer_runs_test.default <- function(data, x, drop = FALSE,
     }
   }
 
-  # compute threshold
   if (!(is.na(threshold))) {
     thresh <- threshold
   } else if (mean == TRUE) {
@@ -86,7 +79,6 @@ infer_runs_test.default <- function(data, x, drop = FALSE,
     thresh <- median(xone, na.rm = TRUE)
   }
 
-  # drop values equal to threshold if drop == TRUE
   if (drop == TRUE) {
     xone <- xone[xone != thresh]
   }
@@ -101,20 +93,15 @@ infer_runs_test.default <- function(data, x, drop = FALSE,
       unlist(use.names = FALSE)
   }
 
-  # compute the number of runs
-  n_runs <- nsignC(x_binary)
-  n1 <- sum(x_binary)
-  n0 <- length(x_binary) - n1
-
-  # compute expected runs and sd of runs
+  n_runs   <- nsignC(x_binary)
+  n1       <- sum(x_binary)
+  n0       <- length(x_binary) - n1
   exp_runs <- expruns(n0, n1)
-  sd_runs <- sdruns(n0, n1)
+  sd_runs  <- sdruns(n0, n1)
 
-  # compute the test statistic
   test_stat <- (n_runs - exp_runs) / (sd_runs ^ 0.5)
   sig <- 2 * (1 - pnorm(abs(test_stat), lower.tail = TRUE))
 
-  # result
   result <- list(
     n = n, threshold = thresh, n_below = n0, n_above = n1,
     mean = exp_runs, var = sd_runs, n_runs = n_runs, z = test_stat,

R/infer-ts-ind-ttest.R

@@ -87,18 +87,17 @@ infer_ts_ind_ttest.default <- function(data, x, y, confint = 0.95,
     stop("x must be a binary factor variable", call. = FALSE)
   }
 
-  method <- match.arg(alternative)
-  var_y <- yone
-  alpha <- 1 - confint
-  a <- alpha / 2
-
-  h <- indth(data, !! x1, !! y1, a)
+  method   <- match.arg(alternative)
+  var_y    <- yone
+  alpha    <- 1 - confint
+  a        <- alpha / 2
+  h        <- indth(data, !! x1, !! y1, a)
   grp_stat <- h
-  g_stat <- as.matrix(h)
-  comb <- indcomb(data, !! y1, a)
-  k <- indcomp(grp_stat, alpha)
-  j <- indsig(k$n1, k$n2, k$s1, k$s2, k$mean_diff)
-  m <- indpool(k$n1, k$n2, k$mean_diff, k$se_dif)
+  g_stat   <- as.matrix(h)
+  comb     <- indcomb(data, !! y1, a)
+  k        <- indcomp(grp_stat, alpha)
+  j        <- indsig(k$n1, k$n2, k$s1, k$s2, k$mean_diff)
+  m        <- indpool(k$n1, k$n2, k$mean_diff, k$se_dif)
 
   result <- list(
     levels = g_stat[, 1], obs = g_stat[, 2], n = k$n,

R/infer-ts-paired-ttest.R

@@ -68,13 +68,8 @@ infer_ts_paired_ttest.default <- function(data, x, y, confint = 0.95,
     select(!! x1, !! y1) %>%
     names()
 
-  xone <-
-    data %>%
-    pull(!! x1)
-
-  yone <-
-    data %>%
-    pull(!! y1)
+  xone <- pull(data, !! x1)
+  yone <- pull(data, !! y1)
 
   k <- paired_comp(xone, yone, confint, var_names)