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Journal of Chinese Integrative Medicine ›› 2012, Vol. 10 ›› Issue (4): 380-383.doi: 10.3736/jcim20120405

• Methodology • Previous Articles     Next Articles

Estimation of sample size and testing power (Part 7)

Liang-ping(),Bao Xiao-lei,Guan Xue   

  1. Consulting Center of Biomedical Statistics, Academy of Military Medical Sciences, Beijing 100850, China
  • Received:2012-02-10 Accepted:2012-02-22 Online:2012-04-20 Published:2018-04-15

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Two-factor factorial design refers to the research involving two experimental factors and the number of the experimental groups equals to the product of the levels of the two experimental factors. In other words, it is the complete combination of the levels of the two experimental factors. The research subjects are randomly divided into the experimental groups. The two experimental factors are performed on the subjects at the same time, meaning that there is no order. The two experimental factors are equal during statistical analysis, that is to say, there is no primary or secondary distinction, nor nested relation. This article introduces estimation of sample size and testing power of quantitative data with two-factor factorial design.

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

Response Variable: SOD"

Cu VE Sample size Mean Standard deviation
0 0 3 331.166 666 7 12.855 478 7
150 3 457.466 666 7 7.852 600 4
0.05 0 3 422.100 000 0 6.937 578 8
150 3 577.066 666 7 7.256 950 7
0.1 0 3 438.533 333 3 22.250 018 7
150 3 580.233 333 3 42.292 355 5
0.2 0 3 441.566 666 7 28.260 455 3
150 3 495.966 666 7 17.696 421 5
0.4 0 3 464.833 333 3 9.557 370 6
150 3 520.133 333 3 28.159 782 2

Fixed Scenario Elements"

Dependent variable Mean
Nominal Power 0.8
Alpha 0.05

Computed N Total"

Index Source Std Dev Test DF Error DF Actual Power N Total
1 Cu 6 4 10 >0.999 20
2 Cu 18 4 10 >0.999 20
3 Cu 30 4 10 0.984 20
4 Cu 42 4 10 0.812 20
5 VE 6 1 10 >0.999 20
6 VE 18 1 10 >0.999 20
7 VE 30 1 10 >0.999 20
8 VE 42 1 10 >0.999 20
9 Cu*VE 6 4 10 >0.999 20
10 Cu*VE 18 4 10 0.940 20
11 Cu*VE 30 4 20 0.812 30
12 Cu*VE 42 4 50 0.877 60

Response Variable： SOD"

Cu VE Sample size Mean Standard deviation
0 0 6 341.450 000 0 15.695 445 2
150 6 463.766 666 7 9.612 006 4
0.05 0 6 413.183 333 3 11.141 708 4
150 6 573.183 333 3 19.615 750 5
0.1 0 6 423.866 666 7 28.221 386 7
150 6 595.783 333 3 45.698 639 7
0.2 0 6 453.133 333 3 61.289 237 8
150 6 495.883 333 3 16.018 915 9
0.4 0 6 459.716 666 7 25.860 581 3
150 6 521.166 666 7 36.075 291 6

Fixed Scenario Elements"

Dependent variable Mean
Total sample size 60
Alpha 0.05
Error degrees of freedom 50

Computed Power"

Index Source Std Dev Test DF Power
1 Cu 9.6 4 >0.999
2 Cu 45.7 4 >0.999
3 VE 9.6 1 >0.999
4 VE 45.7 1 >0.999
5 Cu*VE 9.6 4 >0.999
6 Cu*VE 45.7 4 0.936
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