Difference between revisions of "An initial path towards statistical analysis"
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Relevant figures: <br> | Relevant figures: <br> | ||
+ | Does you categorical dependent variables have 1-2 factor levels? | ||
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+ | Does you categorical dependent variables have more than 2 factor levels? | ||
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+ | ===[[Experiments#Analysis_of_Variance| Analysis of Variance]]<br>=== | ||
+ | R commands: <br> | ||
+ | Relevant figures: <br> | ||
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+ | <div id="Is your dependent variable normally distributed?">The dependent variable is normally distributed</div> | ||
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+ | [[Data_distribution#The_normal_distribution|Dependent variable normally distributed]]<br> | ||
+ | ====[[Type II Anova|Type II Anova]]<br>==== | ||
+ | R commands: <br> | ||
+ | Relevant figures: <br> | ||
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+ | =====[[Poisson GLM|Dependent variable is count data]]===== | ||
+ | R commands: <br> | ||
+ | Relevant figures: <br> | ||
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+ | =====[[Binomial GLM|Dependent variable is 0/1 or proportions]]===== | ||
+ | R commands: <br> | ||
+ | Relevant figures: <br> | ||
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+ | ====[[Linear mixed effect models|Random factors]]==== | ||
+ | R commands: <br> | ||
+ | Relevant figures: <br> | ||
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+ | [[Data_distribution#Non-normal_distributions|Dependent variable not normally distributed]] | ||
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+ | ====[[Type III Anova|Type III Anova]]==== | ||
+ | R commands: <br> | ||
+ | Relevant figures: <br> | ||
+ | |||
+ | =====[[Poisson GLM|Dependent variable is count data]]===== | ||
+ | R commands: <br> | ||
+ | Relevant figures: <br> | ||
+ | |||
+ | =====[[Binomial GLM|Dependent variable is 0/1 or proportions]]===== | ||
+ | R commands: <br> | ||
+ | Relevant figures: <br> | ||
+ | |||
+ | ====[[Generalised linear mixed effect models|Random factors]]==== | ||
+ | R commands: <br> | ||
+ | Relevant figures: <br> | ||
[[#Continuous variables|No, I have only continuous variables! (?)]] (?)<br> | [[#Continuous variables|No, I have only continuous variables! (?)]] (?)<br> | ||
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<div id="Does your independent variable contain more than 2 groups?">Does your independent variable contain more than 2 groups?</div> | <div id="Does your independent variable contain more than 2 groups?">Does your independent variable contain more than 2 groups?</div> | ||
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[[#Is your dependent variable normally distributed?| Is your dependent variable normally distributed?]]<br> | [[#Is your dependent variable normally distributed?| Is your dependent variable normally distributed?]]<br> | ||
[[#Is your dependent variable not normally distributed?|Is your dependent variable not normally distributed?]]<br> | [[#Is your dependent variable not normally distributed?|Is your dependent variable not normally distributed?]]<br> | ||
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Revision as of 20:55, 18 January 2021
Start here with your data! This is your first question.
Do you have several continuous variables without clear dependencies? (?)
Yes!
No!
R commands:
Relevant figures:
Contents
Univariate statistics
Does you data contain at least one categorical variable?
Yes, I have at least one categorical variable! (?) (?)
R commands:
Relevant figures:
Categorical and continuous data
Does your data consist of categorical and continuous variables?
R commands:
Relevant figures:
Does your data consist only of categorical variables?
R commands:
Relevant figures:
Categorical variables
Chi-Square test
R commands:
Relevant figures:
Does you categorical dependent variables have 1-2 factor levels?
Does you categorical dependent variables have more than 2 factor levels?
Analysis of Variance
R commands:
Relevant figures:
Dependent variable normally distributed
Type II Anova
R commands:
Relevant figures:
Dependent variable is count data
R commands:
Relevant figures:
Dependent variable is 0/1 or proportions
R commands:
Relevant figures:
Random factors
R commands:
Relevant figures:
Dependent variable not normally distributed
Type III Anova
R commands:
Relevant figures:
Dependent variable is count data
R commands:
Relevant figures:
Dependent variable is 0/1 or proportions
R commands:
Relevant figures:
Random factors
R commands:
Relevant figures:
No, I have only continuous variables! (?) (?)
R commands:
Relevant figures:
Multivariate statistics
Yes!
Is your dependent variable normally distributed?
Is your dependent variable not normally distributed?
Does your independent variable contain only 1 or 2 groups?
Does your independent variable contain more than 2 groups?
Is your dependent variable normally distributed?
Is your dependent variable not normally distributed?
t-test
Chi-Square test
Continuous variables
Non dependent relations? Correlations
Clear dependent relations
Regression models
Dependent variable normally distributed
Linear Regression
Dependent variable not normally distributed
Dependent variable is count data
Dependent variable is 0/1 or proportions
Resterampe
[[At least one continuous and one categorical variable|
More than 2 groups
Analysis of Variance
Dependent variable normally distributed
INSERT TYPE II
INSERT RANDOM FACTOR
INSERT LMM
Dependent variable not normally distributed
Dependent variable is count data
Dependent variable is 0/1 or proportions