「Regression model」の版間の差分

2022年12月12日 (月) 00:52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

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

@@ 11行目: / 11行目: @@
 !style="width:250px"|Multivariable (multiple variables)
 |-
-!rowspan="2"|Dependent variable<br>(outcome)
+!rowspan="3"|Dependent variable<br>(outcome)
 !Continuous
 |
@@ 28行目: / 28行目: @@
 |
-*'''Logistic regression'''
+*'''Multiple 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
+|-
+!Survival time
+|
+|
+*Multiple proportional hazard regression<br>= Cox hazard regression
 |}