inference {statsr}

Hypothesis tests and confidence intervals

Description

Hypothesis tests and confidence intervals

Usage

inference(
  y,
  x = NULL,
  data,
  type = c("ci", "ht"),
  statistic = c("mean", "median", "proportion"),
  success = NULL,
  order = NULL,
  method = c("theoretical", "simulation"),
  null = NULL,
  alternative = c("less", "greater", "twosided"),
  sig_level = 0.05,
  conf_level = 0.95,
  boot_method = c("perc", "se"),
  nsim = 15000,
  seed = NULL,
  verbose = TRUE,
  show_var_types = verbose,
  show_summ_stats = verbose,
  show_eda_plot = verbose,
  show_inf_plot = verbose,
  show_res = verbose
)

Arguments

y

Response variable, can be numerical or categorical

x

Explanatory variable, categorical (optional)

data

Name of data frame that y and x are in

type

of inference; "ci" (confidence interval) or "ht" (hypothesis test)

statistic

parameter to estimate: mean, median, or proportion

success

which level of the categorical variable to call "success", i.e. do inference on

order

when x is given, order of levels of x in which to subtract parameters

method

of inference; "theoretical" (CLT based) or "simulation" (randomization/bootstrap)

null

null value for a hypothesis test

alternative

direction of the alternative hypothesis; "less","greater", or "twosided"

sig_level

significance level, value between 0 and 1 (used only for ANOVA to determine if posttests are necessary)

conf_level

confidence level, value between 0 and 1

boot_method

bootstrap method; "perc" (percentile) or "se" (standard error)

nsim

number of simulations

seed

seed to be set, default is NULL

verbose

whether output should be verbose or not, default is TRUE

show_var_types

print variable types, set to verbose by default

show_summ_stats

print summary stats, set to verbose by default

show_eda_plot

print EDA plot, set to verbose by default

show_inf_plot

print inference plot, set to verbose by default

show_res

print results, set to verbose by default

Value

Results of inference task performed

Examples

data(tapwater)

# Calculate 95% CI using quantiles using a Student t distribution
inference(tthm, data=tapwater,
                statistic="mean", 
                type="ci",
                method="theoretical")
                
inference(tthm, data=tapwater,
                statistic="mean", 
                type="ci",
                boot_method = "perc",
                method="simulation")
                
# Inference for a proportion
# Calculate 95% confidence intervals for the proportion of atheists

data("atheism")
library("dplyr")
us12 <- atheism %>%
        filter(nationality == "United States" , atheism$year == "2012")
inference(y = response, data = us12, statistic = "proportion",
          type = "ci",
          method = "theoretical", 
          success = "atheist")