| td_tests {terminaldigits} | R Documentation | 
Tests of independence and uniformity for terminal digits in a data frame
Description
The function td_tests() is a wrapper which applies the functionstd_independence() and
td_uniformity to a data frame. When a group is specified, tests are conducted separated
for each group. P-values and p-values adjusted by the false discovery rate (Benjamini
and Hochberg, 1995) are reported.
Usage
td_tests(
  data,
  variable,
  decimals,
  group = NULL,
  reps = 10000,
  test = "Chisq",
  tolerance = 64 * .Machine$double.eps
)
Arguments
| data | A data frame | 
| variable | A numeric variable. Tests for terminal digits are performed on this variable. | 
| decimals | an integer specifying the number of decimals. This can be zero if the terminal digit is not a decimal. | 
| group | A variable used to group the primary variable such that p-values are calculated separately for each group. The default is set to NULL in which case p-values are simply calculated for the whole data set. | 
| reps | an integer specifying the number of Monte Carlo simulations. The default is set to 10,000. | 
| test | a string specifying the test of independence. The default is Pearson's chi-squared statistic ("Chisq"). Also available is the log-likelihood ratio statistic ("G2"), the Freeman-Tukey statistic ("FT"), and the Root-mean-square statistic ("RMS"). | 
| tolerance | sets an upper bound for rounding errors when evaluating
whether a statistic for a simulation is greater than or equal to the
statistic for the observed data. The default is identical to the tolerance
set for simulations in the  | 
Value
A data frame containing the following components:
| statistic | the value of the test statistic | 
| p_value_independence | the simulated p-value for the test of independence | 
| P_value_uniformity | the simulated p-value for the test of uniformity (chi-squared GOF) | 
| p_value_independence_fdr | the simulated p-value for the test of independence adjusted via the
false discovery rate (if the  | 
| P_value_uniformity | the simulated p-value for the test of uniformity (chi-squared GOF)
adjusted via the false discovery rate (if the  | 
References
Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B, 57, 289–300. doi: 10.1111/j.2517-6161.1995.tb02031.x. https://www.jstor.org/stable/2346101.
Examples
td_tests(decoy, weight, decimals = 2, group = subject, reps = 1000)