Find agent skills by outcome

- aov is a wrapper around lm that stores extra info for balanced ANOVA. For unbalanced designs

Type I SS (sequential) are computed — order of terms matters.

- For Type III SS

use car::Anova() or set contrasts to contr.sum/contr.helmert.

- Quasi-families (quasibinomial

quasipoisson) allow overdispersion — no AIC is computed.

- binomial accepts response as: 0/1 vector

logical

- `anova(glm_obj

test = Chisq) for deviance-based tests; F` is invalid for non-Gaussian families.

- weights in glm means prior weights (not frequency weights) — for frequency weights

use the cbind trick or offset.

- Column names from model.matrix can be surprising: e.g.

factorLevelName concatenation.

- Common families: binomial(link = logit)

poisson(link = log)

- Default family = gaussian(link = identity) — glm() with no family silently fits OLS (same as lm

but slower and with deviance-based output).

- I() is required to use arithmetic operators literally: y ~ x + I(x^2). Without I()

^ means interaction crossing.

- terms object attributes: order (interaction order per term)

intercept

Creative

- model.matrix creates the design matrix including dummy coding. Default contrasts: contr.treatment...

contr.poly for ordered.

- Captures output from cat

Non-obvious behaviors

gotchas

- Converts character vectors to appropriate types (logical

integer

- as.is = TRUE (recommended): keeps characters as character

not factor.

- `formatC(x

format = f

- Assignment form: `substr(x

- `format(x

digits

- which = both (default)

left

- `substring(x

first

Creative

- `substr(x

start

- Common mistake: unnamed arguments silently match fixed

perl

- Three regex modes: POSIX extended (default)

perl = TRUE