nursingHomes: Wisconsin Nursing Homes Utilization Data

In copulaData: Data Sets for Copula Modeling

Description

Data set containing the occupancy rate (utilization) and covariates of 377 nursing homes in Wisconsin between 1995 and 2001.

Usage

data("nursingHomes")

Format

data.frame containing the nursing home identification number (ID), the occupancy rate (Rate; see Sun et al. (2008, Equation (7)) for how this is computed), the logarithmic number of beds of the nursing home (LnNumBed), the logarithmic net square foot of the nursing home (LnSqrFoot), the cost report year (CRYear), indicators whether the nursing home runs on a for-profit basis (Pro), whether it is tax exempt (TaxExempt), whether it has self funding of insurance (SelfIns), whether it is accredited as Medicare Certified (MCert) and whether it is located in an urban environment (Urban); see Sun et al. (2008, Table 2).

Source

Edward W. Frees, Wisconsin Department of Health and Family Services (by now named “Wisconsin Department of Health Services”)

References

Sun, J., Frees, E. W. and Rosenberg, M. A. (2008) Heavy-tailed longitudinal data modeling using copulas. Insurance: Mathematics and Economics 42, 817–830.

Examples

data("nursingHomes")
str(nursingHomes)

Example output

'data.frame':	2497 obs. of  10 variables:
 $ ID       : Factor w/ 377 levels "101","103","105",..: 1 1 1 1 1 1 1 2 2 2 ...
 $ Rate     : num  92.3 90.6 91.4 94.1 93.7 ...
 $ LnNumBed : num  2.89 2.89 2.89 2.89 2.89 ...
 $ LnSqrFoot: num  2.41 2.39 2.39 2.39 2.39 ...
 $ CRYear   : Ord.factor w/ 7 levels "1995"<"1996"<..: 1 2 3 4 5 6 7 1 2 3 ...
 $ Pro      : Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 1 ...
 $ TaxExempt: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 1 1 1 ...
 $ SelfIns  : Factor w/ 2 levels "0","1": 2 2 2 2 2 1 2 2 2 2 ...
 $ MCert    : Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 2 2 2 ...
 $ Urban    : Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 1 ...

copulaData documentation built on May 2, 2019, 6:10 p.m.