clinical trials;
power;
sample size;
multiple treatments;
factorial design;
treatment lag;
multiple comparisons;
Fisher's LSD;
stratification;
Monte Carlo method;
D O I:
10.1016/0169-2607(96)01717-8
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
This paper presents a computer program for use in the design of long-term clinical trials with multiple treatment arms in which the primary outcome variables are censored survival times, The treatment arms may be structured as a one-way or multi-way factorial design. It is assumed that patients are entered and randomized to a treatment arm during an accrual period. The patients are then followed for a fixed period during which there may be dropouts. Various distributional assumptions can be used to model the survival times. These include an option in which there is an effect of treatment duly after a lag or delay time. The program then computes the power of various statistical tests of hypotheses concerning treatment differences, interactions and trends. The power computations are ''exact'' in that they use the Monte Carlo method to obtain Type I and II error probabilities. However the program also outputs the normal approximations for comparison, although they are typically not accurate in these situations. Fisher's LSD method is used to adjust for the multiple comparisons. By comparing the power for various sets of design parameters, such as sample size, numbers of factor levels, patient accrual rate, and length of follow-up, an appropriate design can be constructed. Two examples are provided. The first is a simple one-way layout with multiple treatment arms; the second a two-way factorial design for a proposed large scale cancer chemoprevention trial.
机构:
Univ N Carolina, Dept Biostat, Chapel Hill, NC USA
Univ N Carolina, Dept Biostat, McGavran Greenberg Hall, CB7420, Chapel Hill, NC 27599 USAUniv N Carolina, Dept Biostat, Chapel Hill, NC USA
Bean, Nathan William
Ibrahim, Joseph George
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机构:
Univ N Carolina, Dept Biostat, Chapel Hill, NC USAUniv N Carolina, Dept Biostat, Chapel Hill, NC USA
Ibrahim, Joseph George
Psioda, Matthew Austin
论文数: 0引用数: 0
h-index: 0
机构:
Univ N Carolina, Dept Biostat, Chapel Hill, NC USAUniv N Carolina, Dept Biostat, Chapel Hill, NC USA