--- title: "Use Case IDs" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Use Case IDs} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} bibliography: references.bib csl: apa.csl --- Instead of using row numbers (`case.idx` in the `lavaan` object), `lavaan_rerun()` from the package [semfindr](https://sfcheung.github.io/semfindr/) [@cheung_semfindr_2026] supports user supplied case IDs. This can make the output more readable. ``` r library(semfindr) dat <- pa_dat # Add case id dat <- cbind(id = paste0("case", seq_len(nrow(dat))), dat) head(dat) #> id m1 dv iv1 iv2 #> 1 case1 0.32067106 1.4587148 0.2055776 -0.42187811 #> 2 case2 0.15360231 -0.3809220 0.1853543 0.15229953 #> 3 case3 0.35136439 -0.4886773 0.9151424 1.16670950 #> 4 case4 -0.56529330 -0.9766142 0.2884440 0.04563409 #> 5 case5 -1.60657017 -1.0948066 -0.5756171 -0.18184854 #> 6 case6 0.03143301 0.5859886 0.1420111 0.06286986 ``` Suppose that the data set has a column of case IDs. A model is fitted to this data set using `lavaan::sem()`: ``` r mod <- " m1 ~ iv1 + iv2 dv ~ m1 " library(lavaan) fit <- sem(mod, dat) ``` # Rerun *n* Times We refit the model 100 times, each time with one case removed. Although the `id` column is not stored in `lavaan`, it can be supplied through the argument `case_id`: ``` r fit_rerun <- lavaan_rerun(fit, case_id = dat$id) #> The expected CPU time is 1.5 second(s). #> Could be faster if run in parallel. ``` The list of reruns now uses `id` as the names: ``` r head(fit_rerun$rerun[1:3]) #> $case1 #> lavaan 0.7-2.3166 ended normally after 2 iterations #> #> Estimator ML #> Optimization method NLMINB #> Number of model parameters 5 #> #> Number of observations 99 #> #> Model Test User Model: #> #> Test statistic 6.557 #> Degrees of freedom 2 #> P-value (Chi-square) 0.038 #> #> Browne's residual (NT model-based) test #> Test statistic 6.345 #> Degrees of freedom 2 #> P-value (Chi-square) 0.042 #> #> $case2 #> lavaan 0.7-2.3166 ended normally after 1 iteration #> #> Estimator ML #> Optimization method NLMINB #> Number of model parameters 5 #> #> Number of observations 99 #> #> Model Test User Model: #> #> Test statistic 6.731 #> Degrees of freedom 2 #> P-value (Chi-square) 0.035 #> #> Browne's residual (NT model-based) test #> Test statistic 6.507 #> Degrees of freedom 2 #> P-value (Chi-square) 0.039 #> #> $case3 #> lavaan 0.7-2.3166 ended normally after 1 iteration #> #> Estimator ML #> Optimization method NLMINB #> Number of model parameters 5 #> #> Number of observations 99 #> #> Model Test User Model: #> #> Test statistic 7.128 #> Degrees of freedom 2 #> P-value (Chi-square) 0.028 #> #> Browne's residual (NT model-based) test #> Test statistic 6.878 #> Degrees of freedom 2 #> P-value (Chi-square) 0.032 ``` As shown below, most diagnostic functions will use user supplied case IDs in their displays, making it easier to locate them in the original data set. # Diagnostic Functions ## Standardized Changes in Estimates ``` r fit_est_change <- est_change(fit_rerun) fit_est_change #> #> -- Standardized Case Influence on Parameter Estimates -- #> #> m1~iv1 m1~iv2 dv~m1 m1~~m1 dv~~dv gcd #> case16 0.052 -0.038 -0.237 -0.004 0.624 0.450 #> case43 -0.403 -0.263 -0.135 0.223 0.120 0.302 #> case65 0.152 0.191 0.363 0.076 0.161 0.221 #> case85 -0.174 0.216 -0.119 0.335 -0.052 0.208 #> case51 0.421 -0.057 0.094 0.089 -0.044 0.200 #> case34 -0.314 -0.192 -0.109 0.189 0.030 0.178 #> case32 -0.247 0.195 -0.191 0.193 0.001 0.175 #> case18 -0.273 0.035 0.101 0.260 -0.046 0.156 #> case20 -0.239 0.204 -0.141 0.183 -0.032 0.156 #> case100 -0.001 -0.225 -0.069 0.305 -0.056 0.152 #> #> Note: #> - Changes are standardized raw changes if a case is included. #> - Only the first 10 case(s) is/are displayed. Set 'first' to NULL to display all cases. #> - Cases sorted by generalized Cook's distance. ``` ``` r fit_est_change_paths_only <- est_change(fit_rerun, parameters = c("m1 ~ iv1", "m1 ~ iv2", "dv ~ m1")) fit_est_change_paths_only #> #> -- Standardized Case Influence on Parameter Estimates -- #> #> m1~iv1 m1~iv2 dv~m1 gcd #> case43 -0.403 -0.263 -0.135 0.238 #> case51 0.421 -0.057 0.094 0.190 #> case65 0.152 0.191 0.363 0.189 #> case34 -0.314 -0.192 -0.109 0.142 #> case32 -0.247 0.195 -0.191 0.138 #> case20 -0.239 0.204 -0.141 0.121 #> case85 -0.174 0.216 -0.119 0.093 #> case11 0.010 0.149 -0.257 0.088 #> case18 -0.273 0.035 0.101 0.087 #> case13 0.274 0.059 -0.068 0.082 #> #> Note: #> - Changes are standardized raw changes if a case is included. #> - Only the first 10 case(s) is/are displayed. Set 'first' to NULL to display all cases. #> - Cases sorted by generalized Cook's distance. ``` ## Raw Changes in Estimates ``` r fit_est_change_raw <- est_change_raw(fit_rerun) fit_est_change_raw #> #> -- Case Influence on Parameter Estimates -- #> #> id m1~iv1 id m1~iv2 id dv~m1 id m1~~m1 id dv~~dv #> 1 case51 0.046 case43 -0.026 case65 0.039 case61 0.043 case16 0.108 #> 2 case43 -0.043 case94 0.024 case11 -0.027 case85 0.041 case9 0.051 #> 3 case34 -0.033 case100 -0.022 case16 -0.024 case100 0.038 case76 0.050 #> 4 case13 0.030 case85 0.021 case32 -0.021 case18 0.032 case25 0.050 #> 5 case18 -0.029 case20 0.020 case99 0.020 case42 0.029 case91 0.043 #> 6 case32 -0.026 case32 0.019 case79 0.019 case43 0.028 case17 0.039 #> 7 case20 -0.025 case65 0.019 case93 0.018 case32 0.024 case65 0.030 #> 8 case75 0.021 case34 -0.019 case22 0.017 case34 0.024 case26 0.029 #> 9 case42 -0.020 case64 -0.017 case61 -0.017 case20 0.023 case62 0.027 #> 10 case68 0.020 case52 0.016 case25 -0.015 case40 0.023 case90 0.024 #> #> Note: #> - Changes are raw changes if a case is included. #> - Only the first 10 case(s) is/are displayed. Set 'first' to NULL to display all cases. #> - Cases sorted by the absolute changes for each variable. ``` ## Mahalanobis Distance ``` r fit_md <- mahalanobis_rerun(fit_rerun) fit_md #> #> -- Mahalanobis Distance -- #> #> md #> case16 11.530 #> case99 11.312 #> case87 11.091 #> case43 10.181 #> case51 9.869 #> case13 8.476 #> case91 8.078 #> case71 7.757 #> case17 7.555 #> case68 7.472 #> #> Note: #> - Only the first 10 case(s) is/are displayed. Set 'first' to NULL to display all cases. #> - Cases sorted by Mahalanobis distance in decreasing order. ``` ## Changes in Fit Measures ``` r fit_mc <- fit_measures_change(fit_rerun, fit_measures = c("chisq", "cfi", "tli", "rmsea")) fit_mc #> #> -- Case Influence on Fit Measures -- #> #> chisq cfi tli rmsea #> case1 0.154 -0.002 -0.005 0.002 #> case2 -0.019 0.001 0.003 -0.001 #> case3 -0.417 0.008 0.021 -0.007 #> case4 -0.154 0.004 0.009 -0.003 #> case5 0.097 0.000 0.001 0.001 #> case6 0.116 -0.001 -0.003 0.001 #> case7 -0.631 0.014 0.034 -0.011 #> case8 0.120 0.002 0.005 0.001 #> case9 0.524 -0.012 -0.030 0.008 #> case10 0.697 -0.013 -0.033 0.011 #> #> Note: #> - Only the first 10 case(s) is/are displayed. Set 'first' to NULL to display all cases. ``` ## All-In-One-Function ``` r fit_influence <- influence_stat(fit_rerun) fit_influence #> #> -- Standardized Case Influence on Parameter Estimates -- #> #> m1~iv1 m1~iv2 dv~m1 m1~~m1 dv~~dv gcd #> case16 0.052 -0.038 -0.237 -0.004 0.624 0.450 #> case43 -0.403 -0.263 -0.135 0.223 0.120 0.302 #> case65 0.152 0.191 0.363 0.076 0.161 0.221 #> case85 -0.174 0.216 -0.119 0.335 -0.052 0.208 #> case51 0.421 -0.057 0.094 0.089 -0.044 0.200 #> case34 -0.314 -0.192 -0.109 0.189 0.030 0.178 #> case32 -0.247 0.195 -0.191 0.193 0.001 0.175 #> case18 -0.273 0.035 0.101 0.260 -0.046 0.156 #> case20 -0.239 0.204 -0.141 0.183 -0.032 0.156 #> case100 -0.001 -0.225 -0.069 0.305 -0.056 0.152 #> #> Note: #> - Changes are standardized raw changes if a case is included. #> - Only the first 10 case(s) is/are displayed. Set 'first' to NULL to display all cases. #> - Cases sorted by generalized Cook's distance. #> #> -- Case Influence on Fit Measures -- #> #> chisq cfi rmsea tli #> case1 0.154 -0.002 0.002 -0.005 #> case2 -0.019 0.001 -0.001 0.003 #> case3 -0.417 0.008 -0.007 0.021 #> case4 -0.154 0.004 -0.003 0.009 #> case5 0.097 0.000 0.001 0.001 #> case6 0.116 -0.001 0.001 -0.003 #> case7 -0.631 0.014 -0.011 0.034 #> case8 0.120 0.002 0.001 0.005 #> case9 0.524 -0.012 0.008 -0.030 #> case10 0.697 -0.013 0.011 -0.033 #> #> Note: #> - Only the first 10 case(s) is/are displayed. Set 'first' to NULL to display all cases. #> #> -- Mahalanobis Distance -- #> #> md #> case16 11.530 #> case99 11.312 #> case87 11.091 #> case43 10.181 #> case51 9.869 #> case13 8.476 #> case91 8.078 #> case71 7.757 #> case17 7.555 #> case68 7.472 #> #> Note: #> - Only the first 10 case(s) is/are displayed. Set 'first' to NULL to display all cases. #> - Cases sorted by Mahalanobis distance in decreasing order. ``` # Diagnostic Plots ## Generalized Cook's Distance ``` r gcd_plot(fit_influence, largest_gcd = 3) ``` ![gcd_plot() Example](user_id_gcd_plot_fig-1.png) ## Mahalanobis Distance ``` r md_plot(fit_influence, largest_md = 3) ``` ![md_plot() Example](user_id_md_plot_fig-1.png) ## Fit Measure vs. Generalized Cook's Distance ``` r gcd_gof_plot(fit_influence, fit_measure = "rmsea", largest_gcd = 3, largest_fit_measure = 3) ``` ![gcd_gof_plot() Example](user_id_gcd_gof_plot_fig-1.png) ## Bubble Plot ``` r gcd_gof_md_plot(fit_influence, fit_measure = "rmsea", largest_gcd = 3, largest_fit_measure = 3, largest_md = 3, circle_size = 15) ``` ![gcd_gof_md_plot() Example](user_id_gcd_gof_md_plot_fig-1.png) # References