fil {brlrmr} | R Documentation |
This provides the estimates using IL method and FIL method as described in the reference.
fil(formula, data, parameter = NULL, family = binomial, alpha = 0.05, interaction = FALSE, k = NULL, na.action)
formula |
as in |
data |
as in |
parameter |
The starting values of the parameters as (β, α) where β is the parameters of original model and α is the for the missing data model. |
family |
as in |
alpha |
This is used for upper 100(1 - alpha)% point of standard Normal distribution. The default is 1.96. |
interaction |
TRUE or FALSE, whether to consider interaction in the missing data model. Currenly only one intercation between response and covariates is supported. FALSE by default. |
k |
Which covariate has interaction with response. Takes integer values. User must assign a value if interaction = TRUE. |
na.action |
as in |
n |
number of observations. |
nmissing |
the number of missing observations. |
missing.proportion |
proportion of missing observations. |
beta.hat |
parameter estimate of logistic regression of y on x using FIL method. |
beta.se.hat |
standard error using FIL method. |
z.value |
Wald Z value using FIL method. |
p.value |
p value using FIL method. |
significance.beta.firth |
indicator output whether regressors are significant using FIL method, 1 if significant and 0 if not significant. |
LCL |
Lower Confidence Limits of 100(1 - alpha)% Confidence Intervals. |
UCL |
Upper Confidence Limits of 100(1 - alpha)% Confidence Intervals. |
alpha.hat |
parameter estimate due to missing model using FIL. |
alpha.se.hat |
standard error of the them. |
z.value.alpha |
Wald Z value for them. |
p.value.alpha |
p values for them. |
Bias Reduction in Logistic Regression with Missing Responses when the Missing Data Mechanism is Nonignorable.
## Not run: ############################################# ########### Simulated Example ############### ############################################# data(simulated.data) # load simulated data # parameter definition beta0 <- 1 beta1 <- 1 beta2 <- 1 beta3 <- 1 beta4 <- 1 # parameter definition for missing indicator alpha0 <- -1.1 alpha1 <- -1 alpha2 <- 1 alpha3 <- 1 alpha4 <- 1 alpha5 <- -1 parameter <- c(beta0, beta1, beta2, beta3, beta4, alpha0, alpha1, alpha2, alpha3, alpha4, alpha5) fil(y ~ x1 + x2 + x3 + x4, data = simulated.data, parameter, family = binomial(link = "logit"), na.action = na.pass) ## End(Not run) ############################################# ##### Real data example with separation ##### ############################################# data(nhanes) # load nhanes data fil(hyp ~ age2 + age3, data = nhanes, family = binomial(link = "logit"), na.action = na.pass) data(incontinence) # load nhanes data fil(y ~ x1 + x2 + x3, data = incontinence, family = binomial(link = "logit"), na.action = na.pass)