dftorep: Transform a Dataframe to a repeated Object

Description

dftorep forms an object of class, repeated, from a dataframe with the option of removing any observations where response and covariate values have NAs. For repeated measurements, observations on the same individual must be together in the table. A number of validity checks are performed on the data.

Such objects can be printed and plotted. Methods are available for extracting the response, the numbers of observations per individual, the times, the weights, the units of measurement/Jacobian, the nesting variable, the covariates, and their names: response, nobs, times, weights, delta, nesting, covariates, and names.

Usage

dftorep(dataframe, response, id=NULL, times=NULL, censor=NULL,
	totals=NULL, weights=NULL, nest=NULL, delta=NULL,
	coordinates=NULL, type=NULL, ccov=NULL, tvcov=NULL, na.rm=TRUE)

Value

Returns an object of class, repeated, containing a list of the response object (z$response, so that, for example, the response vector is z$response$y; see restovec), and possibly the two classes of covariate objects (z$ccov and z$tvcov; see tcctomat and tvctomat).

Arguments

dataframe

A dataframe.

response

A character vector giving the column name(s) of the dataframe for the response variable(s).

id

A character vector giving the column name of the dataframe for the identification numbers of the individuals. If the numbers are not consecutive integers, a warning is given.

If NULL, one observation per individual is assumed if times is also NULL, other time series is assumed.

times

An optional character vector giving the column name of the dataframe for the times vector.

censor

An optional character vector giving the column name(s) of the dataframe for the censor indicator(s). This must be the same length as response. Responses without censor indicator can have a column either of all NAs or all 1s.

totals

An optional character vector giving the column name(s) of the dataframe for the totals for binomial data. This must be the same length as response. Responses without censor indicator can have a column all NAs.

weights

An optional character vector giving the column name of the dataframe for the weights vector.

nest

An optional character vector giving the column name of the dataframe for the nesting vector within individuals.

This is the second level of nesting for repeated measurements, with the individual being the first level. Values for an individual must be consecutive increasing integers.

delta

An optional character vector giving the column name(s) of the dataframe for the units of measurement/Jacobian(s) of the response(s). This must be the same length as response. Responses without units of measurement/Jacobian can have a column all NAs.

If all response variables have the same unit of measurement, this can be that one number. If each response variable has the same unit of measurement for all its values, this can be a numeric vector of length the number of response variables.

coordinates

An optional character vector giving the two or three column name(s) of the dataframe for the spatial coordinates.

type

An optional character vector giving the types of response variables: nominal, ordinal, discrete, duration, continuous, multivariate, or unknown.

ccov

An optional character vector giving the column names of the dataframe for the time-constant or inter-individual covariates. For repeated measurements, if the value is not constant for all observations on an individual, an error is produced.

tvcov

An optional character vector giving the column names of the dataframe for the time-varying or intra-individual covariates.

na.rm

If TRUE, observations with NAs in any variables selected are removed in the object returned. Otherwise, the corresponding indicator variable is returned in a slot in the object.

Author

J.K. Lindsey

Examples

Run this code

y <- data.frame(y1=rpois(20,5),y2=rpois(20,5))
y[2,2] <- NA
idd <- c(rep(1,5),rep(2,10),rep(3,5))
tt <- c(1:5,1:10,1:5)
totals <- data.frame(tot1=rep(12,20),tot2=rep(12,20))
x2 <- c(rep(1,5),rep(2,10),rep(3,5))
df <- data.frame(y,id=idd,tt=tt,totals,x1=rnorm(20),x2=x2)
df
dftorep(df,resp=c("y1","y2"),times="tt",id="id",totals=c("tot1","tot2"),
	tvcov="x1",ccov="x2")
dftorep(df,resp=c("y1","y2"),times="tt",id="id",totals=c("tot1","tot2"),
	tvcov="x1",ccov="x2",na.rm=FALSE)
# x1 is not a time-constant covariate
#dftorep(df,resp=c("y1","y2"),times="tt",id="id",ccov="x1",na.rm=FALSE)