# Convert Parameter Syntax to Position or Row Numbers in the Parameter Vector or Table Converts a vector of lavaan syntax to the ids of parameters in the vector of free parameters or the row numbers in the parameter table. ```r pars_id(pars, fit, where = c("coef", "partable"), free_only = TRUE) ``` ## Arguments - `pars`: A character vector of parameters specified in lavaan syntax, e.g., `"y ~ x"` and `f1 =~ x3`. For multisample models, if only the parameters in some groups are needed, use the modifier for labeling parameters and use `NA` to denote parameters to be requested. E.g., `f1 =~ c(NA, 0, NA, NA) * x2` denotes the loadings of `x2` on `f1` in the first, third, and fourth groups. - `fit`: A `lavaan`-class object. This object is used to determine the number of groups and the parameters in the model. Only parameters in `pars` that appear in this model will be considered. - `where`: Where the values are to be found. Can be "partable" (parameter table) or "coef" (coefficient vector). Default is "coef". - `free_only`: Whether only free parameters will be kept. Default is `TRUE`. ## Returns A numeric vector of the ids. If `where` is `"partable"`, the ids are row numbers. If `where` is `"coef"`, the ids are the positions in the vector. ## Details It supports the following ways to specify the parameters to be included. * `lavaan` syntax * For example, `"y ~ x"` denotes the regression coefficient regression `y` on `x`. It uses `lavaan::lavaanify()` to parse the syntax strings. * Operator * For example, `"~"` denotes all regression coefficients. * It also supports `:=`, which can be used to select user-defined parameters. * Label * For example, `"ab"` denotes all parameters with this labels defined in model syntax. It can be used to select user-defined parameters, such as `"ab := a*b"`. It is used by functions such as `est_change()`. ### Multisample model If a model has more than one group, a specification specified as in a single sample model denotes the same parameters in all group. * For example, `"f1 =~ x2"` denotes the factor loading of `x2` on `f1` in all groups. `"~~"` denotes covariances and error covariances in all groups. There are two ways to select parameters only in selected groups. First, the syntax to fix parameter values can be used, with `NA` denoting parameters to be selected. * For example, `"f2 =~ c(NA, 1, NA) * x5"` selects the factor loadings of `x5` on `f2` in the first and third groups. Users can also add ".grouplabel" to a specification, `grouplabel` being the group label of a group (the one appears in `summary()`, not the one of the form `".g2"`, `"g3"`, etc.). * For example, `"f2 =~ x5.Alpha"` denotes the factor loading of `x5` on `f2` in the group `"Alpha"`. * This method can be used for operators. For example, `"=~.Alpha"` denotes all factors loadings in the group `"Alpha"`. Though not recommended, users can use labels such as `".g2"` and `".g3"` to denote the parameter in a specific group. These are the labels appear in the output of some functions of `lavaan`. Although `lavaan` does not label the parameters in the first group by `".g1"`, this can still be used in `pars_id()`. * For example, `"f2 =~ x5.g2"` denotes the factor loading of `x5` on `f2` in the second group. `"y ~ x.g1"` denotes the regression coefficient from `x` to `y` in the first group. * This method can also be used for operators. For example, `"=~.g2"` denotes all factors loadings in the second group. However, this method is not as reliable as using `grouplabel` because the numbering of groups depends on the order they appear in the data set. ## Examples ```r dat <- sem_dat library(lavaan) sem_model <- " f1 =~ x1 + x2 + x3 f2 =~ x4 + x5 + x6 f3 =~ x7 + x8 + x9 f2 ~ f1 f3 ~ f2 " fit_ng <- sem(sem_model, dat) pars <- c("f1 =~ x2", "f2 =~ x5", "f2 ~ f1") tmp <- pars_id(pars, fit = fit_ng) coef(fit_ng)[tmp] tmp <- pars_id(pars, fit = fit_ng, where = "partable") parameterTable(fit_ng)[tmp, ] # Multiple-group models dat <- sem_dat set.seed(64264) dat$gp <- sample(c("Alpha", "Beta", "Gamma"), nrow(dat), replace = TRUE) library(lavaan) sem_model <- " f1 =~ x1 + x2 + x3 f2 =~ x4 + x5 + x6 f3 =~ x7 + x8 + x9 f2 ~ f1 f3 ~ f2 " fit_ng <- sem(sem_model, dat) fit_gp <- sem(sem_model, dat, group = "gp") pars <- c("f1 =~ x2", "f2 =~ x5", "f2 ~ f1") tmp <- pars_id(pars, fit = fit_ng) coef(fit_ng)[tmp] tmp <- pars_id(pars, fit = fit_ng, where = "partable") parameterTable(fit_ng)[tmp, ] pars <- c("f1 =~ x2", "f2 =~ c(NA, 1, NA) * x5") tmp <- pars_id(pars, fit = fit_gp) coef(fit_gp)[tmp] tmp <- pars_id(pars, fit = fit_gp, where = "partable") parameterTable(fit_gp)[tmp, ] pars2 <- c("f1 =~ x2", "~~.Beta", "f2 =~ x5.Gamma") tmp <- pars_id(pars2, fit = fit_gp) coef(fit_gp)[tmp] tmp <- pars_id(pars2, fit = fit_gp, where = "partable") parameterTable(fit_gp)[tmp, ] # Note that group 1 is "Beta", not "Alpha" lavInspect(fit_gp, "group.label") ``` ## Author(s) Shu Fai Cheung [https://orcid.org/0000-0002-9871-9448](https://orcid.org/0000-0002-9871-9448)

pars_id function