Fit Simple Mediation Model for Data with Beta X - Ordinary Least Squares — beta_fit.ols • jeksterslabRmedsimple

Fit Simple Mediation Model for Data with Beta X - Ordinary Least Squares

beta_fit.ols(data, taskid)

Arguments

data	`n` by 3 matrix or data frame. `data[, 1]` correspond to values for `x`. `data[, 2]` correspond to values for `m`. `data[, 3]` correspond to values for `y`.
taskid	Numeric. Task ID.

See also

Other model fit functions: beta_fit.ols_simulation_summary(), beta_fit.ols_simulation(), beta_fit.ols_task_summary(), beta_fit.ols_task(), beta_fit.sem.mlr_simulation_summary(), beta_fit.sem.mlr_simulation(), beta_fit.sem.mlr_task_summary(), beta_fit.sem.mlr_task(), beta_fit.sem.mlr(), beta_std_fit.sem.mlr_simulation_summary(), beta_std_fit.sem.mlr_simulation(), beta_std_fit.sem.mlr_task_summary(), beta_std_fit.sem.mlr_task(), beta_std_fit.sem.mlr(), exp_fit.ols_simulation_summary(), exp_fit.ols_simulation(), exp_fit.ols_task_summary(), exp_fit.ols_task(), exp_fit.ols(), exp_fit.sem.mlr_simulation_summary(), exp_fit.sem.mlr_simulation(), exp_fit.sem.mlr_task_summary(), exp_fit.sem.mlr_task(), exp_fit.sem.mlr(), exp_std_fit.sem.mlr_simulation_summary(), exp_std_fit.sem.mlr_simulation(), exp_std_fit.sem.mlr_task_summary(), exp_std_fit.sem.mlr_task(), exp_std_fit.sem.mlr(), fit.cov(), fit.ols(), fit.sem.mlr(), fit.sem(), mvn_fit.ols_simulation_summary(), mvn_fit.ols_simulation(), mvn_fit.ols_task_summary(), mvn_fit.ols_task(), mvn_fit.ols(), mvn_fit.sem_simulation_summary(), mvn_fit.sem_simulation(), mvn_fit.sem_task_summary(), mvn_fit.sem_task(), mvn_fit.sem(), mvn_mar_10_fit.sem_simulation_summary(), mvn_mar_10_fit.sem_simulation(), mvn_mar_10_fit.sem_task_summary(), mvn_mar_10_fit.sem_task(), mvn_mar_10_fit.sem(), mvn_mar_20_fit.sem_simulation_summary(), mvn_mar_20_fit.sem_simulation(), mvn_mar_20_fit.sem_task_summary(), mvn_mar_20_fit.sem_task(), mvn_mar_20_fit.sem(), mvn_mar_30_fit.sem_simulation_summary(), mvn_mar_30_fit.sem_simulation(), mvn_mar_30_fit.sem_task_summary(), mvn_mar_30_fit.sem_task(), mvn_mar_30_fit.sem(), mvn_mcar_10_fit.sem_simulation_summary(), mvn_mcar_10_fit.sem_simulation(), mvn_mcar_10_fit.sem_task_summary(), mvn_mcar_10_fit.sem_task(), mvn_mcar_10_fit.sem(), mvn_mcar_20_fit.sem_simulation_summary(), mvn_mcar_20_fit.sem_simulation(), mvn_mcar_20_fit.sem_task_summary(), mvn_mcar_20_fit.sem_task(), mvn_mcar_20_fit.sem(), mvn_mcar_30_fit.sem_simulation_summary(), mvn_mcar_30_fit.sem_simulation(), mvn_mcar_30_fit.sem_task_summary(), mvn_mcar_30_fit.sem_task(), mvn_mcar_30_fit.sem(), mvn_mnar_10_fit.sem_simulation_summary(), mvn_mnar_10_fit.sem_simulation(), mvn_mnar_10_fit.sem_task_summary(), mvn_mnar_10_fit.sem_task(), mvn_mnar_10_fit.sem(), mvn_mnar_20_fit.sem_simulation_summary(), mvn_mnar_20_fit.sem_simulation(), mvn_mnar_20_fit.sem_task_summary(), mvn_mnar_20_fit.sem_task(), mvn_mnar_20_fit.sem(), mvn_mnar_30_fit.sem_simulation_summary(), mvn_mnar_30_fit.sem_simulation(), mvn_mnar_30_fit.sem_task_summary(), mvn_mnar_30_fit.sem_task(), mvn_mnar_30_fit.sem(), mvn_std_fit.sem_simulation_summary(), mvn_std_fit.sem_simulation(), mvn_std_fit.sem_task_summary(), mvn_std_fit.sem_task(), mvn_std_fit.sem(), vm_mod_fit.ols_simulation_summary(), vm_mod_fit.ols_simulation(), vm_mod_fit.ols_task_summary(), vm_mod_fit.ols_task(), vm_mod_fit.ols(), vm_mod_fit.sem.mlr_simulation_summary(), vm_mod_fit.sem.mlr_simulation(), vm_mod_fit.sem.mlr_task_summary(), vm_mod_fit.sem.mlr_task(), vm_mod_fit.sem.mlr(), vm_mod_std_fit.sem.mlr_simulation_summary(), vm_mod_std_fit.sem.mlr_simulation(), vm_mod_std_fit.sem.mlr_task_summary(), vm_mod_std_fit.sem.mlr_task(), vm_mod_std_fit.sem.mlr(), vm_sev_fit.ols_simulation_summary(), vm_sev_fit.ols_simulation(), vm_sev_fit.ols_task_summary(), vm_sev_fit.ols_task(), vm_sev_fit.ols(), vm_sev_fit.sem.mlr_simulation_summary(), vm_sev_fit.sem.mlr_simulation(), vm_sev_fit.sem.mlr_task_summary(), vm_sev_fit.sem.mlr_task(), vm_sev_fit.sem.mlr(), vm_sev_std_fit.sem.mlr_simulation_summary(), vm_sev_std_fit.sem.mlr_simulation(), vm_sev_std_fit.sem.mlr_task_summary(), vm_sev_std_fit.sem.mlr_task(), vm_sev_std_fit.sem.mlr()

Author

Ivan Jacob Agaloos Pesigan

Examples

taskid <- 1
data <- beta_dat(taskid = taskid)
beta_fit.ols(data = data, taskid = taskid)
#>                    taskid                         n                      reps 
#>              1.000000e+00              1.000000e+03              5.000000e+03 
#>                    taudot                      beta                     alpha 
#>              1.414214e-01              7.140742e-01              7.140742e-01 
#>                 alphabeta                   sigma2x            sigma2epsilonm 
#>              5.099020e-01              6.250000e-02              3.063113e-02 
#>            sigma2epsilony                       mux                    deltam 
#>              2.036725e-02              5.000000e-01              1.429629e-01 
#>                    deltay                 deltayhat                 taudothat 
#>              7.225223e-02              9.402306e-02              1.305995e-01 
#>                   betahat                 deltamhat                  alphahat 
#>              6.930495e-01              1.626804e-01              6.754568e-01 
#>           alphahatbetahat            taudothatprime              betahatprime 
#>              4.681250e-01              1.368583e-01              6.961998e-01 
#>             alphahatprime alphahatprimebetahatprime                sigma2xhat 
#>              7.046244e-01              4.905593e-01              6.468484e-02 
#>      sigma2hatepsilonmhat      sigma2hatepsilonyhat                    muxhat 
#>              2.995854e-02              2.138373e-02              4.991395e-01 
#>            sehatdeltayhat            sehattaudothat              sehatbetahat 
#>              1.107952e-02              2.563634e-02              2.674337e-02 
#>            sehatdeltamhat             sehatalphahat     sehattaudothatprimetb 
#>              1.206078e-02              2.153160e-02              2.686493e-02 
#>       sehatbetahatprimetb      sehatalphahatprimetb  sehattaudothatprimedelta 
#>              2.686493e-02              2.246138e-02              2.680997e-02 
#>    sehatbetahatprimedelta   sehatalphahatprimedelta 
#>              2.344390e-02              1.593019e-02