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how to choose correct statistics methods 1  

2011-11-22 03:28:25|  分类: 生物信息编程 |  标签: |举报 |字号 订阅

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Number

of 
Dependent* 
Variables

Number 
of 
Independent** 
Variables

Type 
of 
Dependent 
Variable(s)

Type 
of 
Independent 
Variable(s)

 Measure

Test(s)

1

 0 
(1 population)

continuous normal

not applicable  
(none)

 mean

one-sample t-test

 continuous non-normal

 median

one-sample median

 categorical

 proportions

 Chi Square goodness-of-fit, binomial test

 1 
(2 independent populations)

normal

 2 categories

 mean

2 independent sample t-test

 non-normal

medians

 Mann Whitney, 
Wilcoxon rank sum test

 categorical

 proportions

 Chi square test 
Fisher's Exact test


(1 population measured twice) 
or 

(2 matched populations)

normal

 not applicable/ 
categorical

means

paired t-test 

 non-normal

 medians

Wilcoxon signed ranks test 

 categorical

 proportions

McNemar, Chi-square test


(3 or more populations)

normal

categorical

means

one-way ANOVA

non-normal

medians

Kruskal Wallis

categorical

proportions

Chi square test

2 or more 
(e.g., 2-way ANOVA)

normal

categorical

means

Factorial ANOVA

non-normal

medians

Friedman test

categorical

proportions

log-linear, logistic regression


(1 population measured  
3 or more times)

normal

not applicable

means

Repeated measures ANOVA

1

normal

continuous

correlation 
simple linear regression

non-normal

 non-parametric correlation

categorical

categorical or continuous

logistic regression

continuous

discriminant analysis

 2 or more

 normal

continuous

multiple linear regression 

 non-normal

 

categorical

logistic regression

normal

mixed categorical and continuous

Analysis of Covariance 
General Linear Models (regression)

 non-normal

 

categorical

logistic regression

2

2 or more

normal

categorical

MANOVA

2 or more

2 or more

normal

continuous

multivariate multiple linear regression

2 sets of  
2 or more

0

normal

not applicable

canonical correlation

2 or more

0

normal

not applicable

factor analysis

 

  

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