umx (version 4.0.0)

xmuRAM2Ordinal: xmuRAM2Ordinal

Description

xmuRAM2Ordinal: Convert a RAM model whose data contain ordinal variables to a threshold-based model

Usage

xmuRAM2Ordinal(model, verbose = TRUE, name = NULL)

Arguments

model

An RAM model to add thresholds too.

verbose

Tell the user what was added and why (Default = TRUE).

name

= A new name for the modified model. Default (NULL) = leave it as is).

Value

See Also

Other xmu internal not for end user: umxModel(), umxRenameMatrix(), umxTwinMaker(), umx_APA_pval(), umx_fun_mean_sd(), umx_get_bracket_addresses(), umx_make(), umx_standardize(), umx_string_to_algebra(), umx, xmuHasSquareBrackets(), xmuLabel_MATRIX_Model(), xmuLabel_Matrix(), xmuLabel_RAM_Model(), xmuMI(), xmuMakeDeviationThresholdsMatrices(), xmuMakeOneHeadedPathsFromPathList(), xmuMakeTwoHeadedPathsFromPathList(), xmuMaxLevels(), xmuMinLevels(), xmuPropagateLabels(), xmuTwinSuper_Continuous(), xmuTwinUpgradeMeansToCovariateModel(), xmu_CI_merge(), xmu_CI_stash(), xmu_DF_to_mxData_TypeCov(), xmu_PadAndPruneForDefVars(), xmu_cell_is_on(), xmu_check_levels_identical(), xmu_check_needs_means(), xmu_check_variance(), xmu_clean_label(), xmu_data_missing(), xmu_data_swap_a_block(), xmu_describe_data_WLS(), xmu_dot_make_paths(), xmu_dot_make_residuals(), xmu_dot_maker(), xmu_dot_move_ranks(), xmu_dot_rank_str(), xmu_extract_column(), xmu_get_CI(), xmu_lavaan_process_group(), xmu_make_TwinSuperModel(), xmu_make_bin_cont_pair_data(), xmu_make_mxData(), xmu_match.arg(), xmu_name_from_lavaan_str(), xmu_path2twin(), xmu_path_regex(), xmu_safe_run_summary(), xmu_set_sep_from_suffix(), xmu_show_fit_or_comparison(), xmu_simplex_corner(), xmu_standardize_ACEcov(), xmu_standardize_ACEv(), xmu_standardize_ACE(), xmu_standardize_CP(), xmu_standardize_IP(), xmu_standardize_RAM(), xmu_standardize_SexLim(), xmu_standardize_Simplex(), xmu_start_value_list(), xmu_starts(), xmu_twin_add_WeightMatrices(), xmu_twin_check(), xmu_twin_get_var_names(), xmu_twin_upgrade_selDvs2SelVars()

Examples

Run this code
# NOT RUN {
data(twinData)
# Cut to form category of 20% obese subjects
obesityLevels   = c('normal', 'obese')
cutPoints       = quantile(twinData[, "bmi1"], probs = .2, na.rm = TRUE)
twinData$obese1 = cut(twinData$bmi1, breaks = c(-Inf, cutPoints, Inf), labels = obesityLevels) 
twinData$obese2 = cut(twinData$bmi2, breaks = c(-Inf, cutPoints, Inf), labels = obesityLevels) 
ordDVs = c("obese1", "obese2")
twinData[, ordDVs] = umxFactor(twinData[, ordDVs])
mzData = twinData[twinData$zygosity %in% "MZFF",]
m1 = umxRAM("tim", data = mzData,
	umxPath("bmi1", with = "bmi2"),
	umxPath(v.m.= c("bmi1", "bmi2"))
)

m1 = umxRAM("tim", data = mzData,
	umxPath("obese1", with = "obese2"),
	umxPath(v.m.= c("obese1", "obese2"))
)
# }

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