semnova: Semnova class

In langenberg/semnova: Analyzing Interindividual Differences in Experiments

Semnova class

Description

Some description

Usage

semnova(...)

semnova_dummy(...)

## S3 method for class 'Semnova'
Effect(focal.predictors, mod, ...)

## S3 method for class 'Semnova'
plot(mod, focal.predictors, ...)

## S3 method for class 'Semnova'
coefficients(object, ...)

coef.Semnova(object, ...)

Details

semnova() is a wrapper for the R6 class constructor Semnova$new(). See Semnova$new() below for a list of arguments.

Super class

semnova::Lgc -> Semnova

Methods

Public methods

• Semnova$get_model_matrix()

• Semnova$new()

• Semnova$specify()

• Semnova$specify_dummy()

• Semnova$clone()

Inherited methods

• semnova::Lgc$anova()
• semnova::Lgc$belongs_to()
• semnova::Lgc$compare()
• semnova::Lgc$estimate()
• semnova::Lgc$fit_measures()
• semnova::Lgc$get_covariates_mmodel()
• semnova::Lgc$get_data()
• semnova::Lgc$get_estimates()
• semnova::Lgc$get_etas_mmodel()
• semnova::Lgc$get_facet_grid()
• semnova::Lgc$get_labels()
• semnova::Lgc$get_lav_syntax()
• semnova::Lgc$has_covariate()
• semnova::Lgc$has_latent_covariate()
• semnova::Lgc$has_latent_dv()
• semnova::Lgc$has_resid_cov()
• semnova::Lgc$has_within()
• semnova::Lgc$is_indicator()
• semnova::Lgc$is_latent()
• semnova::Lgc$power_analysis()
• semnova::Lgc$print()
• semnova::Lgc$reliabilities()
• semnova::Lgc$set_data()
• semnova::Lgc$summary()
• semnova::Lgc$test()
• semnova::Lgc$tests_table()

---

Method get_model_matrix()

Usage

Semnova$get_model_matrix(dat = NULL)

---

Method new()

Semnova class constructor.

Usage

Semnova$new()

---

Method specify()

Specifies a Semnova object.

Usage

Semnova$specify(
  data,
  id,
  dv,
  indicators = NULL,
  withins = NULL,
  betweens = NULL,
  contrasts_arg = list(),
  resid_cov = list(),
  equal_resid_cov = list(),
  sphericity = list(),
  covariates = NULL,
  normalize_contrasts = FALSE,
  ...
)

Arguments

data

tibble. Will be converted to tibble if not already a tibble.

id

Character vector. Variables from the data set that uniquely identify each case.

dv

Character. Variable from the data set that contains the dependent variable.

indicators

Character. Variable from the data set that contains indicators measuring the latent dependent eta variables.

withins

Character vector. Variables from the data set that contain within-subject factors.

betweens

Character vector. Variables from the data set that contain between-subject factors.

contrasts_arg

Named list of characters. Each element specifies the contrast coding scheme for the within or between subject factors. Names of the list elements indicate the factor.

resid_cov

List of character vectors. Each character vector contains manifest variables from the data set among which residual covariances should be implemented. Residual covariances can vary.

equal_resid_cov

List of character vectors. Each character vector contains manifest variables from the data set among which residual covariances should be implemented. Residual covariances are constrained to be equal.

sphericity

List of character vectors or formula. If list: Each element contains factor names for which sphericity should be imposed; If formula: Left-hand side is either TRUE or FALSE. If left-hand side is TRUE, sphericty is assumed except for effect names occuring on the right-hand side. If FALSE, sphericty is NOT assumed except for effect names occuring on the right-hand side.

covariates

Named list of character vectors. Each list element (character vector) represents an covairate variable. The elements of the character vector are manifest variables (i.e., indicators) from the data set that measure the corresponding covariate. The list names correspond to the names of the covariates. E.g.: covariates = list( covariate1 = c("covariate11", "covariate12"), covariate2 = c("covariate21", "covariate22"), covariate3 = c("covariate31", "covariate32") )

normalize_contrasts

Logical. Indicates whether contrasts should be scaled to length equal to one.

...

Parameters passed to the Lgc Class constructor.

compound_symmetry

Logical. Indicates whether compound symmetry should be imposed.

---

Method specify_dummy()

Specifies a Semnova object.

Usage

Semnova$specify_dummy(
  n_within = 1,
  n_between = 1,
  n_indicator = 1,
  n_latent_covariate = NULL,
  n_manifest_covariate = NULL,
  contrasts_arg_within = NULL,
  contrasts_arg_between = NULL,
  contrasts_arg_covariate = NULL,
  sphericity = NULL,
  resid_cov = NULL,
  equal_resid_cov = NULL,
  ...
)

---

Method clone()

The objects of this class are cloneable with this method.

Usage

Semnova$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

langenberg/semnova documentation built on Feb. 12, 2025, 7:06 a.m.