oohbsyn: Synthetic data set for oohbchoice()

In DCchoice: Analyzing Dichotomous Choice Contingent Valuation Data

Description

Dataset created artificially for the examples section of the function oohbhoice().

Usage

data(oohbsyn)

Format

A data frame with 80 observations on the following variables.

id

a vector of the identification number of the respondent.

gender

a vector containing the gender of the respondent, taking male or female.

age

a vector containing the age of the respondent.

BL

a vector of lower bid.

BH

a vector of higher bid.

R1

a vector of response to the first stage CV question, taking a value of 1 if the bid is accepted, and 0 otherwise.

R2

a vector of response to the second stage CV question, taking a value of 1 if the bid is accepted, 0 if the bid is not accepted, and -9 if the respondent has no the second stage question.

See Also

oohbchoice, turnbull.oohb

Examples

## Parametric model
data(oohbsyn)
oohb1 <- oohbchoice(R1 + R2 ~ 1 | log(BL) + log(BH), data = oohbsyn)
summary(oohb1)
oohb2 <- oohbchoice(R1 + R2 ~ age + gender | log(BL) + log(BH), data = oohbsyn)
summary(oohb2)

## Non-parametric model
oohb3 <- turnbull.oohb(R1 + R2 ~ BL + BH, data = oohbsyn)
summary(oohb3)
plot(oohb3)

Example output

Loading required package: MASS
Loading required package: interval
Loading required package: survival
Loading required package: perm
Loading required package: Icens
Loading required package: MLEcens
Loading required package: Formula

Call:
oohbchoice(formula = R1 + R2 ~ 1 | log(BL) + log(BH), data = oohbsyn)

Formula:
R1 + R2 ~ 1 | log(BL) + log(BH)

Coefficients: 
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)   4.6665     0.9674   4.824    1e-06 ***
log(bid)     -2.5628     0.5246  -4.885    1e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Distribution: log-logistic 
Number of Obs.: 80 
Log-likelihood: -70.391865 

LR statistic: -0.000 on 0 DF, p-value: 1.000 
AIC: 144.783731 , BIC: 149.547784 

Iterations: 13 6 
Convergence: TRUE 

WTP estimates:
 Mean : 8.04642 
 Mean : 6.359207 (truncated at the maximum bid)
 Mean : 8.209596 (truncated at the maximum bid with adjustment)
 Median: 6.177279 

Call:
oohbchoice(formula = R1 + R2 ~ age + gender | log(BL) + log(BH), data = oohbsyn)

Formula:
R1 + R2 ~ age + gender | log(BL) + log(BH)

Coefficients: 
             Estimate Std. Error z value Pr(>|z|)    
(Intercept)  4.718799   1.305157  3.6155   0.0003 ***
age         -0.003988   0.022967 -0.1737   0.8621    
gendermale   0.203367   0.453933  0.4480   0.6541    
log(bid)    -2.565100   0.524818 -4.8876    1e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Distribution: log-logistic 
Number of Obs.: 80 
Log-likelihood: -70.277697 

LR statistic: 0.228 on 2 DF, p-value: 0.892 
AIC: 148.555394 , BIC: 158.083500 

Iterations: 27 8 
Convergence: TRUE 

WTP estimates:
 Mean : 8.031227 
 Mean : 6.353733 (truncated at the maximum bid)
 Mean : 8.193918 (truncated at the maximum bid with adjustment)
 Median: 6.168739 
Survival probability: 
   Upper   Prob.
1      0  1.0000
2      2  0.9058
3      4  0.7646
4      6  0.5497
5      8  0.3113
6     10  0.1868
7    Inf  0.0000

WTP estimates:
 Mean: 5.436373  (Kaplan-Meier)
 Mean: 6.249617  (Spearman-Karber)
 Median in: [       6 ,       8 ] 

DCchoice documentation built on May 2, 2019, 4:44 p.m.