linbin2stg {missreg}R Documentation

Estimate binary-logistic parameters and odds ratios using linear regression with a single continuous Y-variable for two-phase sampled data.

Description

Fit location-scale model of the form Y = eta + sigma*error to data with a single continuous Y-variable and two-phase missingness structure, and convert to binary-logistic parameters and odds-ratio estimates with appropriate cut-points of Y.

Usage

linbin2stg(formula1, yCuts, lower.tail = TRUE, weights = NULL, 
        xstrata = NULL, data = list(), obstype.name = "obstype", 
        fit = TRUE, xs.includes = FALSE, compactX = FALSE, 
        start = NULL, Qstart = NULL, deltastart = NULL, 
        int.rescale = TRUE, control = mlefn.control(...), 
        control.inner = mlefn.control.inner(...), ...)

Arguments

formula1 A symbolic description of the location model to be fitted, i.e. eta.
yCuts Cutpoint(s) used to define the binary Y-variable for logistic regression. Can be a matrix form (1*S) with S the number of xstrata.
lower.tail If TRUE, define the cases being {Y <= yCuts}.
weights An optional vector of weights to be used in the fitting process. Should be NULL or a numeric vector.
xstrata Specify names of the stratification variables to be used, e.g. "vname" or c("vname1","vname2",...). Strata are defined by cross-classification of all levels.
data A data frame containing all the variables required for analysis, including those for xstrata and obstype.name.
obstype.name Name of the variable specifying labels for observations by sampling and variable type: "uncond", "retro", "xonly", "y|x" or "strata".
fit If FALSE, only stratum report will be generated without model fitting.
xs.includes TRUE if weights specified for observations labelled as "strata" include those observed at the second phase (i.e. "retro" or "uncond" observations).
compactX If TRUE, compress X matrix to distinct values with counts before model fitting.
start Starting values for the regression parameters. Can be compusory if the program cannot produce a valid starting value at some situations.
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.
deltastart An optional starting matrix for Pr(X=xk|Xstratum=j).
int.rescale If TRUE, all X-variables will be standardised first before fitted in the model.
control Specify control parameters for the iterations in mlefn call. See mlefn for details.
control.inner Specify control parameters for inner iterations nested within mlefn call. See mlefn for details.
... Further arguments passed to or from related functions.

Details

This function is a simple application of locsc2stg fitting linear regression models with a continuous Y using logistic error distribution. The results are then converted to much more efficient inferences about the same odds-ratio parameters being estimated by the logistic regression with the dichotomized binary outcome (case-control).

More detailed descriptions of this function can be found in "Description of the missreg Library" (Wild and Jiang).

Value

missReport Matrix containing information on deleted records with missing observations.
StrReport Cross tabulation of counts for different levels of obstype and Y-values by X-strata.
xStrReport Cross tabulation of counts for obstype by X-strata when obstype="xonly".
key Specify detailed classification for each of the X-strata.
yCutsKey Specify the cutoff intervals for defined Y-strata within each X-stratum.
fit TRUE or FALSE as its argument.
error The error messages returned by mlefn call. Non-zero values indicate an unsuccessful fit.
coefficients Linear regression coefficients.
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.
fitted The fitted values of Y obtained from the model.
cov The asymptotic covariance matrix (inverse of the informnation matrix) of linear parameter estimates.
cor The asymptotic correlation matrix of linear parameter estimates.
bcoefficients Binary regression coefficients converted from linear parameters.
bcov The asymptotic variance of binary parameter estimates.

Note

The function summary.linbin2stg provides a complete summary of the regression results including the Wald tests and a regression panel for linear coefficients, a regression panel for binary coefficients, and associated odds-ratio estimates and confidence intervals. All related output functions (print.linbin2stg, summary.linbin2stg and print.summary.linbin2stg) don't have help files provided at the moment.

Also note that the intercept of binary coefficients will not be available when more than one cut-point of Y is used, e.g. different for each x-stratum.

Author(s)

Chris Wild, Yannan Jiang

References

Description of the missreg Library, Wild and Jiang, 2007.

See Also

locsc2stg

Examples

data(lowbirth.ls)
lowbirth.ls$sex.age <- interaction(lowbirth.ls$sex,lowbirth.ls$gest)
yCuts <- matrix(c(2550,2650,2740,2840,2900,3010,3030,3140),nrow=1)
yCut1 <- mean(yCuts)
 
### Multiple yCuts;
z1 <- linbin2stg(birthwt~gest+mumht+bmi+ethnicdb+hyper+smoke, 
                  yCuts=yCuts, xstrata=c("sex.age"), data=lowbirth.ls, 
                  obstype.name=c("instudy"), xs.includes=FALSE)

summary(z1)

### Single yCut;
z2 <- linbin2stg(birthwt~gest+mumht+bmi+ethnicdb+hyper+smoke, 
                  yCuts=yCut1, xstrata=c("sex.age"), data=lowbirth.ls, 
                  obstype.name=c("instudy"), xs.includes=FALSE)

summary(z2)
[Package missreg version 2.0.1 Index]