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Deprecated functions in the apastats2 package

Source: R/deprecated.R
apastats-deprecated.Rd

These functions are deprecated and will be removed in a future version. Please use their replacements as indicated.

  • describe.ttest -> apa (for t.test objects)

  • describe.r -> apa (for cor.test objects)

  • describe.chi -> apa (for chisq.test objects)

  • describe.mean.sd -> apa_mean_sd

  • describe.mean.conf -> apa_mean_conf

  • describe.binom.mean.conf -> apa_binom_mean_conf

  • describe.mean.and.t -> apa_mean_and_t

  • describe.Anova -> apa (for Anova objects)

  • describe.aov -> apa (for aov objects)

  • describe.anova -> apa (for anova objects)

  • describe.afex -> apa (for afex_aov objects)

  • describe.bf -> apa (for BFBayesFactor objects)

  • describe.brm -> apa (for brmsfit objects)

  • describe.dip.test -> apa (for dip.test objects)

  • describe.emmeans -> apa (for emmeans objects)

  • describe.ezanova -> apa (for ezanova objects)

  • describe.ezstats -> apa (for ezstats objects)

  • describe.glm -> apa (for glm/lm objects)

  • describe.lht -> apa (for linearHypothesis objects)

  • describe.lmer -> apa (for lmer objects)

  • describe.lmert -> apa (for lmerTest objects)

  • describe.lmtaov -> apa (for lmerTest anova objects)

  • describe.lsmeans -> apa (for lsmeans objects)

  • describe.roc.diff -> apa (for ROC difference objects)

  • mean.nn -> mean_nn

  • sd.nn -> sd_nn

  • sum.nn -> sum_nn

  • drop.empty.cols -> drop_empty_cols

  • binom.ci -> binom_ci

  • mean.round -> mean_round

  • sd.round -> sd_round

  • load.libs -> load_libs

  • lmer.fixef -> lmer_fixef

  • omit.zeroes -> omit_zeroes

  • f.round -> f_round

  • base.breaks -> base_breaks

  • base.breaks.x -> base_breaks_x

  • base.breaks.y -> base_breaks_y

  • plot.pointrange() -> plot_pointrange

  • mymean -> mean_nn

  • mysum -> sum_nn

  • mysd -> sd_nn

Usage

describe.ttest(t, ...)

describe.r(rc, ...)

describe.chi(tbl, ...)

describe.Anova(afit, term, f.digits = 2, ...)

describe.aov(fit, term = NULL, sstype = 2, ...)

describe.anova(anova_res, rown = 2, f.digits = 2, ...)

describe.afex(
  afex_fit,
  term,
  include_eta = TRUE,
  eta_digits = 2,
  f_digits = 2,
  df_digits = 0,
  append_to_table = FALSE,
  ...
)

describe.bf(bf, digits = 2, top_limit = 10000, convert_to_power = TRUE, ...)

describe.brm(
  mod,
  term,
  trans = NULL,
  digits = 2,
  eff.size = FALSE,
  eff.size.type = "r",
  nsamples = 100,
  ci.type = "HPDI",
  ...
)

describe.dip.test(x, ...)

describe.emmeans(obj, term, dtype = "B", df = FALSE, ...)

describe.ezanova(
  ezfit,
  term,
  include_eta = TRUE,
  spher_corr = TRUE,
  eta_digits = 2,
  f_digits = 2,
  df_digits = 0,
  append_to_table = FALSE,
  ...
)

describe.ezstats(ezstats_res, term = 1, ...)

describe.glm(
  fit,
  term = NULL,
  dtype = 1,
  b.digits = 2,
  t.digits = 2,
  test.df = FALSE,
  p.as.number = FALSE,
  term.pattern = NULL,
  eff.size = FALSE,
  adj.digits = FALSE,
  ...
)

describe.lht(hyp, ...)

describe.lmer(
  fm,
  pv,
  digits = c(2, 2, 2),
  incl.rel = 0,
  dtype = "B",
  incl.p = TRUE
)

describe.lmert(sfit, factor, dtype = "t", ...)

describe.lmtaov(afit, term, f.digits = 2, ...)

describe.lsmeans(obj, term, dtype = "B", df = FALSE, ...)

describe.roc.diff(roc_diff)

describe.mean.sd(
  x = NULL,
  m = NULL,
  sd = NULL,
  digits = 2,
  dtype = "p",
  m_units = "",
  sd_units = "",
  ...
)

describe.mean.conf(
  x,
  bootCI = TRUE,
  addCI = FALSE,
  digits = 2,
  transform.means = NULL,
  ...
)

describe.binom.mean.conf(x, digits = 2, ...)

describe.mean.and.t(
  x,
  by,
  which.mean = 1,
  digits = 2,
  paired = FALSE,
  eff.size = FALSE,
  abs = FALSE,
  aggregate_by = NULL,
  transform.means = NULL,
  ...
)

mymean(...)

mysum(...)

mysd(...)

# S3 method for class 'nn'
mean(x, ...)

sd.nn(x, ...)

# S3 method for class 'nn'
sum(x, ...)

drop.empty.cols(df)

binom.ci(x)

# S3 method for class 'round'
mean(x, ...)

sd.round(x, ...)

load.libs(libs)

lmer.fixef(fit.lmer)

omit.zeroes(x, digits = 2)

f.round(x, digits = 2, strip.lead.zeros = FALSE)

base.breaks(x, scale = "x", addSegment = TRUE, ...)

base.breaks.x(x, addSegment = TRUE, ...)

base.breaks.y(x, addSegment = TRUE, ...)

# S3 method for class 'pointrange'
plot(
  data,
  mapping,
  pos = position_dodge(0.3),
  pointsize = I(3),
  linesize = I(1),
  pointfill = I("white"),
  pointshape = NULL,
  within_subj = FALSE,
  wid = "uid",
  bars = "ci",
  withinvars = NULL,
  betweenvars = NULL,
  x_as_numeric = FALSE,
  custom_geom_before = NULL,
  connecting_line = FALSE,
  pretty_breaks_y = FALSE,
  pretty_y_axis = FALSE,
  exp_y = FALSE,
  print_aggregated_data = FALSE,
  do_aggregate = FALSE,
  add_margin = FALSE,
  margin_label = "all",
  margin_x_vals = NULL,
  bars_instead_of_points = FALSE,
  geom_bar_params = list(),
  add_jitter = FALSE,
  individual_points_params = list(),
  drop_NA_subj = FALSE,
  design = "between",
  debug = FALSE
)

Value

Each function returns the result of its replacement and signals a deprecation warning. The returned value depends on the function:

  • The describe.* functions return character vectors containing APA-formatted statistical results, such as test statistics, degrees of freedom, p-values, effect sizes, means, or confidence intervals. describe.glm and describe.lmer instead return a data frame when no term is selected, with formatted coefficient summaries in columns B, SE, Stat, p, eff, and str; see apa.glm for the column meanings. With append_to_table = TRUE, describe.afex and describe.ezanova instead return a data frame containing the selected ANOVA results and an additional res column with formatted text.

  • mymean, mean.nn, mysum, sum.nn, mysd, and sd.nn return numeric summaries (mean, sum, or standard deviation) with missing values removed.

  • drop.empty.cols returns the input data frame with columns containing only missing values removed.

  • binom.ci returns a named numeric vector: y is the estimated proportion, ymin and ymax are its confidence limits, and len is the number of observations.

  • mean.round, sd.round, omit.zeroes, and f.round return character vectors containing formatted numbers.

  • load.libs invisibly returns a list of logical values, one per requested package, indicating whether loading succeeded. It is called for the side effect of loading and attaching packages.

  • lmer.fixef returns a data frame with columns Estimate, Std.Err, and t, giving fixed-effect estimates, standard errors, and estimate-to-standard-error ratios.

  • base.breaks, base.breaks.x, and base.breaks.y return a continuous ggplot2 scale (class ScaleContinuousPosition) with axis breaks; when addSegment = TRUE, they return a list containing a segment layer and that scale.

  • plot.pointrange returns a ggplot object showing group summaries with confidence intervals or standard errors.