






Enter data in
yellow boxes, hit "submit button" and answers will appear
on the next page in blue boxes  graphs of data
below.





WTP_1

WTP_2

WTP_3

WTP_4

WTP_5



WTP Threshold >










Z (alpha/2)=


Z value for probability 

<
Prob of type I error (alpha)or



Z (beta)=


Z value for probability of
Type II error


< Prob of type II error (beta)or




sdet=


standard deviation of the effect in
treatment group



sdec=


standard deviation
of the effect in control group



sdct=


standard deviation
of the cost in treatment group



sdcc=


standard deviation
of the cost in control group



dC=


mean difference in cost



dE=


mean difference in effect



Corr_dEdC


correlation between
difference in cost and difference in effect









Sample
Size Calculator  Results  number needed in each arm based on data entered
above.




WTP_1

WTP_2

WTP_3

WTP_4

WTP_5



N =



















Power Analysis



If
the study has already been completed, this section below calculates the power
to detect a difference, if a difference actually exists,



based on the numbers entered in the
first group of yellow boxes above.




N_1

N_2

N_3

N_4

N_5



Study Sample Size









1Z_beta








Power = (prob(1Z_beta))












Figure 1. Below is a graph example illustrating the data results generated by the HDS sample size calculator.This shows the sample size by willingness to pay and by different values of the correlation between cost and effect. Note the "effect only" line which is constant. 




Figure 2. Below is a graph example illustrating the data results generated by the HDS sample size calculator.This shows the sample size by willingness to pay and by different values of power. Note the "effect only" line which is constant.






Figure 3. Below is a graph example illustrating the data results generated by the HDS power calculator.This shows the power by sample size for different values of the correlation between cost and effect. 







References:





Briggs
A and Gray A. Power and sample size calculations for stochastic



costeffectiveness analysis. Med
Decis Making 1998: 18 suppl:S81S92.




Briggs A and Tambour M. The design
and analysis of stochastic



costeffectiveness studies for the
evaluation of health care interventionsl.



Stockholm School of Economics.
Working paper #234. April 1998.




Walter SD et al. Estimation, power
and sample size calculations for



stochastic cost and effectiveness
analysis. Pharmacoeconomics



2007; 25(6):455466.




Glick H et al. Economic evaluation
in clinical trials. Oxford University



Press, 2007.

