「Regression model」の版間の差分

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!style="width:250px"|Multivariable (multiple variables)
 
!style="width:250px"|Multivariable (multiple variables)
 
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!rowspan="3"|Dependent variable<br>(outcome)
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!rowspan="4"|Dependent variable<br>(outcome)
 
!Continuous
 
!Continuous
 
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*'''Multivariable linear regression'''
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*'''Multiple&dagger; linear regression'''
 
::<math>Y = a + b_1X_1 + b_2X_2 + b_3X_3 + \cdots</math>
 
::<math>Y = a + b_1X_1 + b_2X_2 + b_3X_3 + \cdots</math>
  
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!Binary
 
!Binary
 
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*'''Simple logistic regression'''
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*'''Simple binary logistic regression'''
 
::<math>\log Y = a + bX</math><br>where <math>Y</math> is odds of outcome
 
::<math>\log Y = a + bX</math><br>where <math>Y</math> is odds of outcome
  
 
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*'''Multiple logistic regression'''
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*'''Multiple&dagger; binary logistic regression'''
 
::<math>\log Y = a + b_1X_1 + b_2X_2 + b_3X_3 + \cdots</math><br>where <math>Y</math> is odds of outcome
 
::<math>\log Y = a + b_1X_1 + b_2X_2 + b_3X_3 + \cdots</math><br>where <math>Y</math> is odds of outcome
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!Multinominal<br>&ge; 3
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*'''Simple multinominal logistic regression'''
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*'''Multiple&dagger; multinominal logistic regression'''
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!Ordinal
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*'''Simple ordinal logistic regression'''
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*'''Multiple&dagger; ordinal logistic regression'''
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!Survival time
 
!Survival time
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*'''Multiple proportional hazard regression'''<br>= '''Cox hazard regression'''
 
*'''Multiple proportional hazard regression'''<br>= '''Cox hazard regression'''
 
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&dagger;'Multiple' can be rephrased as 'Multivariable'; <color="red">'''NOT 'Multivariate'!!'''<color="red">

2022年12月12日 (月) 01:07時点における版

Basics & Definition
Epidemiology
Odds in statistics and Odds in a horse race
Collider bias
Data distribution
Statistical test
Regression model
Multivariate analysis
Marginal effects
Prediction and decision
Table-related commands in STATA
Missing data and imputation

Classification of Regression models

Independent variable (exposure)
Monovariable (single variable) Multivariable (multiple variables)
Dependent variable
(outcome)
Continuous
  • Simple linear regression
[math]\displaystyle{ Y = a + bX }[/math]
  • Multiple† linear regression
[math]\displaystyle{ Y = a + b_1X_1 + b_2X_2 + b_3X_3 + \cdots }[/math]
Binary
  • Simple binary logistic regression
[math]\displaystyle{ \log Y = a + bX }[/math]
where [math]\displaystyle{ Y }[/math] is odds of outcome
  • Multiple† binary logistic regression
[math]\displaystyle{ \log Y = a + b_1X_1 + b_2X_2 + b_3X_3 + \cdots }[/math]
where [math]\displaystyle{ Y }[/math] is odds of outcome
Multinominal
≥ 3
  • Simple multinominal logistic regression
  • Multiple† multinominal logistic regression
Ordinal
  • Simple ordinal logistic regression
  • Multiple† ordinal logistic regression
Survival time
  • Multiple proportional hazard regression
    = Cox hazard regression

†'Multiple' can be rephrased as 'Multivariable'; <color="red">NOT 'Multivariate'!!<color="red">