| rclusbin {missreg} | R Documentation |
Fits random intercept models to clustered binary data with the two-phase missingness structure.
rclusbin(formula, weights = NULL, ClusInd = NULL, IntraClus = NULL,
xstrata = NULL, ystrata = NULL, obstype.name = "obstype",
data, NMat = NULL, xs.includes = FALSE, MaxInClus = NULL,
rmsingletons = FALSE, retrosamp = "proband", gamma = NULL,
fit = TRUE, linkname = "logit", start = NULL, Qstart = NULL,
sigma = NULL, control = mlefn.control(...),
control.inner = mlefn.control.inner(...), ...)
formula |
A symbolic description of the model to be fitted. |
weights |
An optional vector of weights to be used in the fitting
process. Should be NULL or a numeric vector.
It provides weights at the individual level when there are clusters of size greater than one. When all clusters are of size one, it provides weights at cluster=individual level. |
ClusInd |
A vector specifying cluster membership. Can be
NULL if all clusters are of size one. |
IntraClus |
A vector specifying intra-cluster sequence of individual subjects in a cluster. The one with the smallest i.d. is treated as the proband who were originally sampled into a study. |
xstrata |
Specify names of the stratification variables to be used,
e.g. "vname" or c("vname1","vname2",...).
Strata are defined by cross-classifiction of all levels.
This function only deals with the situation when clusters are defined within xstrata. |
ystrata |
Specify name of the variable defing the Y-strata. Compulsory when gamma probabilities are used (see Details for more descriptions). |
obstype.name |
Name of the variable specifying labels for observations
by sampling and variable type: "uncond", "retro",
"xonly", "y|x" or "strata". |
data |
A data frame containing all the variables required for analysis,
including those for xstrata, ystrata and
obstype.name. |
NMat |
Population counts in a matrix form with rows and columns
corresponding to Y-strata and X-strata respectively.
Should not be provided when there is any observation of
the type "strata". |
xs.includes |
TRUE if weights specified for obervations
labelled as "strata" include those observed at the second
phase (i.e. "retro" or "uncond" observations). |
MaxInClus |
A value specifying the maximum number of individuals allowed
in a cluster. Set to NULL if there is no limit. |
rmsingletons |
If TRUE, remove clusters of size one. |
retrosamp |
Three restrospective sampling schemes can be applied based on
the Y-status of all subjects in the same cluster: "proband",
"allcontrol" and "gamma" (see Details for more
descriptions). The default is "proband". |
gamma |
A vector of length 2 specifying the probabilities that individuals
belong to Y=1 based on their cluster status (see Details for
more descriptions). |
fit |
If FALSE, only stratum report will be generated without
model fitting. |
linkname |
A specification for the model link function. Three choices are
provide: "logit", "probit" or "cloglog". The default
is "logit". |
start |
Starting values for the regression parameters. The first p-coefficients
are parameters for X-variables. The last parameter is for the random
intercept term and normally denoted as w=log(sigma). The program
cannot provide starting values for all data strctures so will force
you to use this whenever it is necessary. |
Qstart |
An optional starting matrix for Pr(Ystratum=i|Xstratum=j). Can be compulsory if the program cannot produce a valid starting value at some situations. |
sigma |
An optional starting value for sigma. The default value (when set to
NULL) is 0.5. |
control |
Specify control parameters for the iterations in mlefn call. |
control.inner |
Specify control parameters for inner iterations nested within
mlefn call. |
... |
Further arguments passed to or from related function. |
This function fits binary regression models with a random intercept of the form
a_i=e^{w*eps_i} where w=log(sigma) and eps_i is standard normal for each cluster,
along with a linear predictor eta_{ij}=x_{ij}^T*beta for the subject j in the i^th
cluster.
The function can be applied to both prospective and retrospective data with
various types of observations collected at different two-phase sampling schemes.
Three retrospective samplings are considered with the Y-strata defined as:
(1) the case-control status of the proband only ("proband");
(2) the case-cotnrol status of all members in the same cluster ("allcontrol").
If any one of the members are cases, the cluster belongs to Y-strata=1 and
otherwise Y-strata=0;
(3) the case-control status of all members in the same cluster plus the gamma
probabilities ("gamma"). The conditional probability of Y-strata=1 depends
on sum_j{Y_j}=1 (with gamma_1 probability) or sum_j{Y_j}>1
(with gamma_2 probability). Here Y_j indicates case-control status
(1 for a case and 0 for a control) of the j^{th} individual in a cluster.
missReport |
Matrix containing information on deleted records with missing observations. |
StrReport |
Cross tabulation of counts for different levels of obstype
and Y-strata by X-strata. |
xStrReport |
Cross tabulation of counts for obstype by X-strata
when obstype="xonly". |
xkey |
Specify detailed classification for each of the X-strata. |
ykey |
Specify the Y variable and its level that the model is constructed for. |
fit |
TRUE or FALSE as its argument. |
error |
The error messages returned by mlefn call. Non-zero values
indicate an unsuccessful fit. |
coefficients |
The coefficients matrix with estimates, standard errors, z values and associated p-values. |
loglk |
Log-likelihood returned from final mlefn call. |
score |
Score vector returned from final mlefn call. |
inf |
Observed information matrix returned from final mlefn call. |
cov |
The asymptotic covariance matrix (inverse of the information matrix. |
cor |
The asymptotic correlation matrix. |
Qmat |
The estimated Pr(Ystratum=i|Xstratum=j) from the last iteration. |
gamma0 |
The estimated gamma_1 from the data. |
...
The function summary.rclusbin provides a complete summary of the regression
results including the Wald tests and a regression panel. All related output functions
(print.rclusbin, summary.rclusbin and print.summary.rclusbin
don't have help files provided at the moment.
Chris Wild, Yannan Jiang
Description of the missreg Library, Wild and Jiang, 2007.
##### PROSPECTIVE #####
data(leprosypros)
leprosypros$age.trans <- 100*(leprosypros$age+7.5)^(-2)
leprosypros$obstype <- rep("uncond", dim(leprosypros)[1])
z1 <- rclusbin(leprosy~age.trans + scar, weights=counts, data=leprosypros,
linkname="logit", sigma=2.5)
summary(z1)
##### RETROSPECTIVE #####
data(brainpairs)
brainpairs$obstype <- rep("retro", dim(brainpairs)[1])
z2 <- rclusbin(bt ~ ep + ca, ClusInd=id, IntraClus=relid, data=brainpairs)
summary(z2)
data(rdat00)
z3 <- rclusbin(y~x, ClusInd=cluster, data=rdat00, retrosamp="allcontrol")
summary(z3)