data.mb01 data.mb02 data.mb03 data.mb04 data.mb05
data.mb01
data.mb02
data.mb03
data.mb04
data.mb05
Example Datasets for mdmb Package
eval_prior_list() eval_prior_list_sumlog()
eval_prior_list()
eval_prior_list_sumlog()
Evaluates Several Prior Distributions
frm_em() coef(<frm_em>) logLik(<frm_em>) summary(<frm_em>) vcov(<frm_em>) frm_fb() coef(<frm_fb>) plot(<frm_fb>) summary(<frm_fb>) vcov(<frm_fb>) frm2datlist()
frm_em()
coef(<frm_em>)
logLik(<frm_em>)
summary(<frm_em>)
vcov(<frm_em>)
frm_fb()
coef(<frm_fb>)
plot(<frm_fb>)
summary(<frm_fb>)
vcov(<frm_fb>)
frm2datlist()
Factored Regression Model: Generalized Linear Regression Model with Missing Covariates
mdmb-package
Model Based Treatment of Missing Data
yjt_regression() coef(<yjt_regression>) logLik(<yjt_regression>) predict(<yjt_regression>) summary(<yjt_regression>) vcov(<yjt_regression>) bct_regression() coef(<bct_regression>) logLik(<bct_regression>) predict(<bct_regression>) summary(<bct_regression>) vcov(<bct_regression>) logistic_regression() coef(<logistic_regression>) logLik(<logistic_regression>) predict(<logistic_regression>) summary(<logistic_regression>) vcov(<logistic_regression>) oprobit_regression() coef(<oprobit_regression>) logLik(<oprobit_regression>) predict(<oprobit_regression>) summary(<oprobit_regression>) vcov(<oprobit_regression>)
yjt_regression()
coef(<yjt_regression>)
logLik(<yjt_regression>)
predict(<yjt_regression>)
summary(<yjt_regression>)
vcov(<yjt_regression>)
bct_regression()
coef(<bct_regression>)
logLik(<bct_regression>)
predict(<bct_regression>)
summary(<bct_regression>)
vcov(<bct_regression>)
logistic_regression()
coef(<logistic_regression>)
logLik(<logistic_regression>)
predict(<logistic_regression>)
summary(<logistic_regression>)
vcov(<logistic_regression>)
oprobit_regression()
coef(<oprobit_regression>)
logLik(<oprobit_regression>)
predict(<oprobit_regression>)
summary(<oprobit_regression>)
vcov(<oprobit_regression>)
Several Regression Models with Prior Distributions and Sampling Weights
offset_values_extract()
Extracts Offset Values
doprobit() fit_oprobit() coef(<fit_oprobit>) logLik(<fit_oprobit>) summary(<fit_oprobit>) vcov(<fit_oprobit>)
doprobit()
fit_oprobit()
coef(<fit_oprobit>)
logLik(<fit_oprobit>)
summary(<fit_oprobit>)
vcov(<fit_oprobit>)
Ordinal Probit Models
remove_NA_data_frame()
Removes Rows with Some Missing Entries in a Data Frame
yj_trafo() yj_antitrafo() dyjt_scaled() ryjt_scaled() fit_yjt_scaled() coef(<fit_yjt_scaled>) logLik(<fit_yjt_scaled>) summary(<fit_yjt_scaled>) vcov(<fit_yjt_scaled>) bc_trafo() bc_antitrafo() dbct_scaled() rbct_scaled() fit_bct_scaled() coef(<fit_bct_scaled>) logLik(<fit_bct_scaled>) summary(<fit_bct_scaled>) vcov(<fit_bct_scaled>) dt_scaled() rt_scaled() fit_t_scaled() coef(<fit_t_scaled>) logLik(<fit_t_scaled>) summary(<fit_t_scaled>) vcov(<fit_t_scaled>)
yj_trafo()
yj_antitrafo()
dyjt_scaled()
ryjt_scaled()
fit_yjt_scaled()
coef(<fit_yjt_scaled>)
logLik(<fit_yjt_scaled>)
summary(<fit_yjt_scaled>)
vcov(<fit_yjt_scaled>)
bc_trafo()
bc_antitrafo()
dbct_scaled()
rbct_scaled()
fit_bct_scaled()
coef(<fit_bct_scaled>)
logLik(<fit_bct_scaled>)
summary(<fit_bct_scaled>)
vcov(<fit_bct_scaled>)
dt_scaled()
rt_scaled()
fit_t_scaled()
coef(<fit_t_scaled>)
logLik(<fit_t_scaled>)
summary(<fit_t_scaled>)
vcov(<fit_t_scaled>)
Scaled \(t\) Distribution with Yeo-Johnson and Box-Cox Transformations