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Journal of Chinese Integrative Medicine ›› 2012, Vol. 10 ›› Issue (3): 298-302.doi: 10.3736/jcim20120308

• Methodology • Previous Articles     Next Articles

Estimation of sample size and testing power (Part 6)

Hu Liang-ping(),Bao Xiao-lei,Guan Xue,Zhou Shi-guo   

  1. Consulting Center of Biomedical Statistics, Academy of Military Medical Sciences, Beijing 100850, China
  • Received:2011-12-29 Accepted:2011-12-31 Online:2012-03-20 Published:2018-10-10

The design of one factor with k levels (k≥3) refers to the research that only involves one experimental factor with k levels (k≥3), and there is no arrangement for other important non-experimental factors. This paper introduces the estimation of sample size and testing power for quantitative data and qualitative data having a binary response variable with the design of one factor with k levels (k≥3).

Key words: statistics, medical, research design, sample size, testing power, parametric estimation

Fixed scenario elements"

Dependent variable Score
Weight variable CellWgt
Alpha 0.05
Error standard deviation 2.7
Nominal power 0.9

Computed N Total"

Index Type Source Test degree of freedom Error degree of freedom Actual power N total
1 Effect method 2 141 0.906 144
2 Contrast A vs. B 1 459 0.900 462
3 Contrast A vs. C 1 114 0.900 117
4 Contrast B vs. C 1 459 0.900 462

Overall F test for one-way ANOVA"

Fixed Scenario Elements
Method Exact
Alpha 0.05
Group means 11 10 9
Standard deviation 2.7
Group weights 1 1 1
Nominal power 0.9

Computed N Total"

Actual power N total
0.906 144

Overall F test for one-way ANOVA"

Fixed scenario elements
Method Exact
Alpha 0.05
Group means 290 658 763
Group weights 1 1 1
Total sample size 30

Computed power"

Index Standard deviation Power
1 174 >0.999
2 155 >0.999
3 127 >0.999
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