factorH: syntax

Formula syntax at a glance

All high-level functions use standard R model formulas:

response ~ factorA + factorB + factorC

• + lists the main effects.
• Interactions are handled internally, so you do not need to write A:B or A*B.
• The response (left of ~) must be numeric (e.g., a Likert score coded as 1 to 5 and stored as numeric).

Examples below use the included dataset mimicry.

library(factorH)
data(mimicry, package = "factorH")
str(mimicry)

Predictors should be factors. If they are not, the functions will coerce them to factors internally.

What is allowed?

# One factor (KW-style):
liking ~ condition

# Two factors (SRH-style):
liking ~ gender + condition

# Three or more factors (k-way):
liking ~ gender + condition + age_cat

You do not need to write gender:condition or gender*condition. The package constructs the required interaction terms internally when needed.

Numeric response (Likert note)

The response must be numeric. For Likert-type responses (e.g., 1 = strongly disagree, …, 5 = strongly agree), keep the variable numeric. Rank-based procedures can be used with such ordinal-like data.

If a Likert variable has been imported as a factor or character, coerce it safely:

# if stored as character "1", "2", ...:
mimicry$liking <- as.numeric(mimicry$liking)

# if stored as factor with labels "1", "2", ...:
mimicry$liking <- as.numeric(as.character(mimicry$liking))