locsc2stg {missreg}R Documentation

Linear regression with location-scale model for two-phase sampled data.

Description

Fits location-scale model of the form Y = eta1 + exp(eta2)*error to data with a single continuous Y-variable and two-phase missingness structure, using the linear predictors eta1 and eta2 for specification of the location and scale respectively.

Usage

locsc2stg(formula1, formula2, yCuts=NULL, weights=NULL, 
          xstrata=NULL, data=list(), obstype.name="obstype",  
          method="direct", fit=TRUE, errdistrn="logistic", 
          errmodpars=6, xs.includes=FALSE, compactX=FALSE, 
          compactY=TRUE, straty.maxnvals=20, 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 (eta1).
formula2 A symbolic description of the log-scale model to be fitted (eta2). ~1 will fit a constant.
yCuts Cutpoints used to define Y-strata. Critical when method="ycutmeth". Also required when method="direct" but the starting values are not provided (See Details for more descriptions).
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.
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 and obstype.name.
method Two methods are implemented: "ycutmeth" and "direct" (see Details for more descriptions).
fit If FALSE, only stratum report will be generated without model fitting.
errdistrn A specification for the error distribution. Three choices are provided: standard logistic ("logistic"), standard normal ("normal") or student's-t distribution ("t"). The default is "logistic".
errmodpars Set parameter values for the error distribution. The default is 6 for student's-t distribution.
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. This is only applicable to method="direct".
compactY If TRUE, limit the Y-values observed at the first phase (obstype="strata") to limited numbers of equally spaced possible values. This is only applicable to method="direct".
straty.maxnvals If compactY=TRUE, specify the number of equally spaced possible values spanning the range of Y observed as "strata". The default is 20.
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). This is only applicable to method="direct".
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 fits location-scale models to continuous Y using different error distributions with various types of observations collected at different two-phase sampling schemes. More detailed descriptions of this function can be found in "Description of the missreg Library" (Wild and Jiang).




Two methods are implemented with either Y being categorical ("ycutmeth") or at a continuous scale ("direct"). The argument yCuts is critical to the first approach but only required for the second approach when a starting value is needed. If yCuts is a vector, it defines the Y-strata with intervals (-infty, yCuts, infty). If yCuts is a matrix, the number of columns indicates the number of strata used and you can define different cutpoints for each stratum. If you want to have differing numbers of cutpoints for different X-strata, pad out the bottom of any column that is not full with NAs.

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 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.
fitted The fitted values of Y obtained from the model.
cov The asymptotic covariance matrix (inverse of the informnation matrix).
cor The asymptotic correlation matrix.
Qmat The estimated Pr(Ystratum=i|Xstratum=j) from the last iteration.
deltamat The estimated delta matrix from the last iteration.
This is only applicable to method="direct".

Note

The function summary.locsc2stg provides a complete summary of the regression results including the Wald tests and a regression panel. All related output functions (print.locsc2stg, summary.locsc2stg and print.summary.locsc2stg) don't have help files provided at the moment.

Author(s)

Chris Wild, Yannan Jiang

References

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

See Also

bin2stg

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)

z1 <- locsc2stg(birthwt ~ gest + mumht + bmi+ethnicdb+hyper+smoke, ~1,
                yCuts=yCuts, xstrata=c("sex.age"), data=lowbirth.ls, 
                obstype.name=c("instudy"), xs.includes=FALSE, 
                method="ycutmeth")
summary(z1)

z2 <- locsc2stg(birthwt ~ gest + mumht + bmi+ethnicdb+hyper+smoke,~1,
                xstrata=c("sex.age"),data=lowbirth.ls, 
                obstype.name=c("instudy"), xs.includes=FALSE, 
                method="direct", start=z1$coefficients, compactX=TRUE,
                compactY=TRUE, straty.maxnvals=20)
summary(z2)

z2 <- locsc2stg(birthwt ~ gest + mumht + bmi+ethnicdb+hyper+smoke,~1,
                yCuts=yCuts, xstrata=c("sex.age"), data=lowbirth.ls, 
                obstype.name=c("instudy"), xs.includes=FALSE, 
                method="direct", start=z1$coefficients, Qstart=z1$Qmat, 
                compactX=TRUE, compactY=TRUE, straty.maxnvals=20, 
                control.inner=mlefn.control.inner(n.earlyit=3))
summary(z2)

z3 <- locsc2stg(birthwt ~ gest + mumht + bmi+ethnicdb+hyper+smoke,~1,
                xstrata=c("sex.age"),data=lowbirth.ls, 
                obstype.name=c("instudy"), xs.includes=FALSE, 
                method="direct", start=z2$coefficients, 
                deltastart=z2$deltamat, compactX=TRUE,
                compactY=TRUE, straty.maxnvals=100)
summary(z3)

[Package missreg version 2.0.1 Index]