auto_signif_test: Automatic significance test

In LorMe: Lightening One-Code Resolving Microbial Ecology Solution

Automatic significance test

Description

Automatically conduct significance testing

Usage

auto_signif_test(
  data,
  treatment_col,
  value_col,
  paired,
  subject_col,
  prior = FALSE,
  comparison_method = NULL,
  equally_rep = TRUE,
  output = "console",
  output_dir = "./",
  filename = "auto_signif_test",
  report = TRUE
)

Arguments

data	Data frame containing the treatment, value and other information.
treatment_col	Numeric indicating where treatment locates (column number) in data.
value_col	Numeric indicating where treatment value (column number) in data.
paired	Logical indicating whether you want a paired t-test.
subject_col	Only meaningful when Pair is ture. Numeric indicating where subject of treatment (column number) in data.
prior	logical. Whether conducted prior comparisons.
comparison_method	Character string. Only use for more than 2 treatment. Default would automatically choose method. Method of multiple comparison,must be one of "SNK", "Tukey", "bonferroni","LSD" or "Scheffe".
equally_rep	Logical indicating Whether all treatments have same number of replication.
output	A character string indicating output style. Default: "console", which print the report in console. And "file" is available to output report into text-file.
output_dir	Default:"./". Available only when output="file". The direction of output file.
filename	A character string indicating file name of output file. Only work when output set as 'file'.
report	Logical. If print report to console. Default:TRUE

Value

auto_signif_test returns results of significant test and print report in console or file. See details in example.

See results return in t_test_report, wilcox_test_report, anova_report, kruskal_report.

Note

1.when choose output="file", once caused error that terminate the program, use 'sink()' to end the written of exist files.

2.Please confirm your data is in format of dataframe, else may cause bug! (e.g. Do not use 'read.xlsx' to load data into tibble format)

Examples

### Here shows different types of experimental design ###
data("cotton", package = "agricolae")

### Two randomly designed groups ###
sig_results <- auto_signif_test(
  data = cotton,
  treatment_col = 1,
  value_col = 5
)

### Two paired design groups ###
sig_results <- auto_signif_test(
  data = cotton,
  treatment_col = 1,
  value_col = 5,
  paired = TRUE,
  subject_col = 2
)

### More than two randomly designed groups ###
sig_results <- auto_signif_test(
  data = cotton,
  treatment_col = 2,
  value_col = 5
)
head(sig_results)  # Check outputs

### Conduct prior comparisons ###
sig_results <- auto_signif_test(
  data = cotton,
  treatment_col = 2,
  value_col = 5,
  prior = TRUE
)
head(sig_results)  # Check outputs
print(sig_results$basicdata)  # Check statistical summary
print(sig_results$anova_model)  # Extract ANOVA model
print(sig_results$anova_summary)  # Check ANOVA summary
print(sig_results$multiple_comparison_model)  # Extract multiple comparison model
print(sig_results$comparison_results)  # Check between-group comparison
print(sig_results$comparison_letters)  # Check letters (can be used in visualization)

## Change multiple comparison method (maybe not illegal!!)
sig_results <- auto_signif_test(
  data = cotton,
  treatment_col = 2,
  value_col = 5,
  prior = TRUE,
  comparison_method = "LSD"
)
head(sig_results)  # Check outputs
print(sig_results$comparison_letters)  # Note that letters become different

LorMe documentation built on Sept. 13, 2024, 9:07 a.m.