xmuRAM2Ordinal
xmuRAM2Ordinal: Convert a RAM model whose data contain ordinal variables to a threshold-based model
xmuRAM2Ordinal(model, verbose = TRUE, name = NULL)
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). |
Other xmu internal not for end user:
umxModel(),
umxRenameMatrix(),
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(),
xmuTwinSuper_NoBinary(),
xmuTwinUpgradeMeansToCovariateModel(),
xmu_CI_merge(),
xmu_CI_stash(),
xmu_DF_to_mxData_TypeCov(),
xmu_PadAndPruneForDefVars(),
xmu_bracket_address2rclabel(),
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_print_algebras(),
xmu_rclabel_2_bracket_address(),
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_summary_RAM_group_parameters(),
xmu_twin_add_WeightMatrices(),
xmu_twin_check(),
xmu_twin_get_var_names(),
xmu_twin_make_def_means_mats_and_alg(),
xmu_twin_upgrade_selDvs2SelVars()
## 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"))
)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.