configural (version 0.1.5)

jobchar: Meta-analytic correlations of job characteristics with performance and satisfaction

Description

Self-rated job characteristics intercorrelations and correlations with other-rated job performance and self-rated job satisfaction from Humphrey et al. (2007).

Usage

data(jobchar)

Format

list with entries r (mean observed correlations), rho (mean corrected correlations), n (sample sizes), sevar_r (sampling error variances for mean observed correlations), sevar_rho (sampling error variances for mean corrected correlations), and source (character labels indicating which meta-analytic correlations came from the same source)

References

Humphrey, S. E., Nahrgang, J. D., & Morgeson, F. P. (2007). Integrating motivational, social, and contextual work design features: A meta-analytic summary and theoretical extension of the work design literature. Journal of Applied Psychology, 92(5), 1332–1356. tools:::Rd_expr_doi("10.1037/0021-9010.92.5.1332")

Examples

data(jobchar)
predictors <- c('auto', 'skill_var', 'task_var', 'task_sig', 'task_id',
                'fb_job', 'job_comp', 'interdep', 'fb_others', 'soc_support')
sevar_jobchar_perf <-
  cor_covariance_meta(
    r = jobchar$r[c('perform', predictors), c('perform', predictors)],
                    n = jobchar$n[c('perform', predictors), c('perform', predictors)],
                    sevar = jobchar$sevar_r[c('perform', predictors), c('perform', predictors)],
                    rho = jobchar$rho[c('perform', predictors), c('perform', predictors)],
                    sevar_rho = jobchar$sevar_rho[c('perform', predictors),
                                                  c('perform', predictors)],
                    source = jobchar$source[c('perform', predictors), c('perform', predictors)])
cpa_jobchar_perf <- cpa_mat(perform ~ auto + skill_var + task_var + task_sig +
                              task_id + fb_job + job_comp +
                              interdep + fb_others + soc_support,
                            cov_mat = jobchar$rho,
                            n = harmonic_mean(as.vector(jobchar$n[c('perform', predictors),
                                                                  c('perform', predictors)])),
                            se_var_mat = sevar_jobchar_perf,
                            adjust = "pop", conf_level = .95)