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Journal of Chinese Integrative Medicine ›› 2010, Vol. 8 ›› Issue (3): 287-291.doi: 10.3736/jcim20100315

• Medical Statistice • Previous Articles     Next Articles

Statistical analysis for data of multidimensional contingency table with SAS software package (Part five)

Wei-wei Liu , Liang-ping Hu   

  1. Consulting Center of Biomedical Statistics, Academy of Military Medical Sciences, Beijing 100850, China
  • Received:2010-01-24 Accepted:2010-02-25 Online:2010-03-20 Published:2010-03-15
  • Contact: Liang-ping Hu E-mail:lphu812@sina.com

Key words: Statistics, Medicine, Data analysis, Statistical, Qualitative data, SAS software

"

分组 性别 例 数
基因型: GG GA AA
对照组 46 38 9
37 23 7
病例组 104 14 4
68 15 2

"

编号 年龄
(A)
生育史
(B)
收入
(C)
避孕
方法
(Y)
编号 年龄
(A)
生育史
(B)
收入
(C)
避孕
方法
(Y)
1 2 1 2 2 51 2 1 1 1
2 2 1 1 1 52 3 0 2 3
3 1 1 2 2 53 2 1 2 2
49 1 0 2 2 99 3 1 1 1
50 2 1 2 2 100 1 0 2 3

Model information"

Data set Work.Exam1
Response variable c
Number of response levels 3
Weight variable f
Model Generalized logit
Optimization technique Fisher's scoring

Testing global null hypothesis: BETA=0"

Test Chi-square df Pr>ChiSq
Likelihood ratio 42.059 7 4 <0.000 1
Score 41.671 2 4 <0.000 1
Wald 38.814 9 4 <0.000 1

Type 3 analysis of effects"

Effect df Wald chi-square Pr>ChiSq
a 2 38.786 6 <0.000 1
b 2 0.022 0 0.989 1

Analysis of maximum likelihood estimates"

Parameter c df Estimate Standard error Wald chi-square Pr>ChiSq
Intercept 1 1 5.034 4 1.086 1 21.487 4 <0.000 1
Intercept 2 1 1.734 8 1.158 3 2.243 2 0.134 2
a 1 1 -1.709 5 0.497 0 11.830 9 0.000 6
a 2 1 -0.237 5 0.529 2 0.201 5 0.653 5
b 1 1 0.021 9 0.461 0 0.002 2 0.962 2
b 2 1 0.055 4 0.483 4 0.013 1 0.908 8

Odds ratio estimates"

Effect c Point estimate 95% wald confidence limits
a 1 0.181 0.068 0.479
a 2 0.789 0.280 2.225
b 1 1.022 0.414 2.523
b 2 1.057 0.410 2.726

Analysis of maximum likelihood estimates"

Parameter c df Estimate Standard error Wald chi-square Pr>ChiSq
Intercept 1 1 2.502 9 0.252 1 98.578 5 <0.000 1
Intercept 2 1 1.461 6 0.268 1 29.713 0 <0.000 1
a 1 1 1 0.854 8 0.248 5 11.830 9 0.000 6
a 1 2 1 0.118 8 0.264 6 0.201 5 0.653 5
b 1 1 1 -0.010 9 0.230 5 0.002 2 0.962 2
b 1 2 1 -0.027 7 0.241 7 0.013 1 0.908 8
[1] Ge Y, Hu LP . Statistical analysis for data of multidimensional contingency table with SAS software package(Part one)[J]. J Chin Integr Med, 2009,7(11):1086-1089
葛毅, 胡良平 . 高维列联表资料的统计分析与SAS软件实现(一)[J]. 中西医结合学报, 2009,7(11):1086-1089
[2] Ge Y, Hu LP . Statistical analysis for data of multidimensional contingency table with SAS software package(Part two)[J]. J Chin Integr Med, 2009,7(12):1188-1192
葛毅, 胡良平 . 高维列联表资料的统计分析与SAS软件实现(二)[J]. 中西医结合学报, 2009,7(12):1188-1192
[3] Ge Y, Hu LP . Statistical analysis for data of multidimensional contingency table with SAS software package(Part three)[J]. J Chin Integr Med, 2010,8(1):90-94
葛毅, 胡良平 . 高维列联表资料的统计分析与SAS软件实现(三)[J]. 中西医结合学报, 2010,8(1):90-94
[4] Gao H, Hu LP, Guo J, Li CP . Statistical analysis for data of multidimensional contingency table with SAS software package(Part four)[J]. J Chin Integr Med, 2010,8(2):186-189
高辉, 胡良平, 郭晋, 李长平 . 高维列联表资料的统计分析与SAS软件实现(四)[J]. 中西医结合学报, 2010,8(2):186-189
[5] SAS Institute Inc.SAS/Stat 9.2 user’s guide[M].Cary, NC: SAS Institute Inc, 2008: 1091- 1228, 3253-3474
[6] Hu LP. Medical statistics: analysis of quantitative and qualitative data using the triple-type theory[M]. Beijing: People’?s Military Medical Press, 2009: 376-393
胡良平 . 医学统计学——运用三型理论分析定量与定性资料[M]. 北京: 人民军医出版社, 2009: 376-393
[7] Wang JC, Guo ZG. Logistic regression models: methods and application[M]. Beijing: Higher Education Press,2001,(): 249-262
王济川, 郭志刚 . Logistic回归模型——方法与应用[M]. 北京: 高等教育出版社, 2001: 249-262
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