ex3.health{bivpois} |
R Documentation |
Demand for
health care in Australia data (Cameron and Trivedi, 1986). The data refer to the
Australian Health survey for 1977-1978 with sample size equal to 5190.
data(ex3.health)
Dataframe with twenty
variables of length 5190.
No |
Name |
Description |
1 |
doctorco |
Number of consultations with a doctor or specialist in the past 2 weeks |
2 |
prescrib |
Total number of prescribed medications used in past 2 days |
3 |
sex |
1 if female, 0 if male |
4 |
age |
Age in years divided by 100 (measured as mid-point of 10 age groups from
15-19 years to 65-69 with 70 or more coded treated as 72) |
5 |
income |
Annual income in Australian dollars divided by 1000 (measured as mid-point of coded ranges
Nil, <200, 200-1000, 1001-, 2001-, 3001-, 4001-, 5001-, 6001-, 7001-,
8001-10000, 10001-12000, 12001-14000, with 14001- treated as 15000 ). |
6 |
agesq |
AGE squared |
7 |
levyplus |
1 if covered by private health insurance fund for private patient in
public hospital (with doctor of choice), 0 otherwise |
8 |
freepoor |
1 if covered by government because low income, recent immigrant,
unemployed, 0 otherwise |
9 |
freepera |
1 if covered free by government because of old-age or disability
pension, or because invalid veteran or family of deceased veteran, 0 otherwise
(Omitted category LEVY is 1 if covered by Medibank health insurance) |
10 |
illness |
Number of illnesses in past 2 weeks with 5 or more coded as 5 |
11 |
actdays |
Number of days of reduced activity in past two weeks due to illness or
injury |
12 |
hscore |
General health questionnaire score using Goldberg's method. High score
indicates bad health. |
13 |
chcond1 |
1 if chronic condition(s) but not limited in activity, 0 otherwise |
14 |
chcond2 |
1 if chronic condition(s) and limited in activity, 0 otherwise |
15 |
nondocco |
Number of consultations with non-doctor health professionals (chemist,
optician, physiotherapist, social worker, district community nurse,
chiropodist or chiropractor) in the past 2 weeks |
16 |
hospadm |
Number of admissions to a hospital, psychiatric hospital, nursing or
convalescent home in the past 12 months (up to 5 or more admissions which is
coded as 5) |
17 |
hospdays |
Number of nights in a hospital, etc. during most recent admission:
taken, where appropriate, as the mid-point of the intervals 1, 2, 3, 4, 5, 6,
7, 8-14, 15-30, 31-60, 61-79 with 80 or more admissions coded as 80. If no
admission in past 12 months then equals zero. |
18 |
medicine |
Total number of prescribed and nonprescribed medications used in past
2 days |
19 |
nonpresc |
Total number of nonprescribed medications used in past 2 days |
20 |
constant |
Constant term |
Details can be found in
Cameron and Trivedi (1986). This data is used as example three in Karlis and
Ntzoufras (2004). In this illustration two variables are used as response: the
number of consultations with a doctor or a specialist and the total number of
prescribed medications used in past 2 days (doctorco, prescrib). Three
variables have been used as covariates: the gender (1 female, 0 male), the age
in years divided by 100 (measured as midpoints of age groups) and the annual
income in Australian dollars divided by 1000 (measured as midpoint of coded
ranges) {sex, age, income}.
1.
Cameron, A.C. and Trivedi, P.K.
(1986). Econometric Models Based on
Count Data: Comparisons and Applications of
Some Estimators and Tests, Journal of Applied Econometrics, 1,
29 – 54.
2.
Cameron, A.C., Trivedi, P.K.,
Milne, F. and Piggott, J. (1988). A Microeconometric Model of the Demand for
Health Care and Health Insurance in Australia, Review of Economic Studies,
55, 85 – 106.
3.
Cameron, A.C. and Trivedi, P.K.
(1993). Tests of Independence in Parametric Models with Applications and
Illustrations, Journal of Business & Economics Statistics, 11,
29 – 43.
4.
Karlis, D. and Ntzoufras, I. (2004). Bivariate Poisson and Diagonal
Inflated Bivariate Poisson Regression Models in S. (submitted). Technical
Report, Athens University of Economics and Business, Athens, Greece.
5.
Karlis, D. and Ntzoufras, I. (2003). Analysis of Sports Data Using
Bivariate Poisson Models. Journal of the Royal Statistical Society, D,
(Statistician), 52, 381 – 393.
pbivpois
, simple.bp
, lm.bp
, lm.dibp , ex1.sim , ex2.sim , ex4.ita91 .
library(bivpois)
data(ex3.health)
form1<- y1y2~noncommon+(sex+age+income):noncommon
# Bivariate Poisson models
ex3.model.a<-lm.bp('doctorco', 'prescrib', form1, data=ex3.health)
ex3.model.b<-lm.bp('doctorco', 'prescrib', form1, y3~sex, data=ex3.health)
# Double Poisson model
ex3.model.c<-lm.bp('doctorco', 'prescrib', form1, data=ex3.health, zeroL3=T)
# diagonal inflated models
ex3.dibp.a<-lm.dibp('doctorco', 'prescrib', form1, data=ex3.health) # model (a)
ex3.dibp.b<-lm.dibp('doctorco', 'prescrib', form1, y3~sex, data=ex3.health) # model (b)