Compile logistic1 Idrees waris IUGC

LOGISTIC REGRESSION IDREES WARIS 3095

LOGISTIC REGRESSION ,[object Object]

WHY WE USE LOGISTIC ? ,[object Object],[object Object],[object Object],[object Object]

TYPES OF LOGISTIC REGRESSION ,[object Object],[object Object],[object Object],[object Object]

BINARY LOGISTIC REGRESSION EXPRESSION Y = Dependent Variables ß ˚ = Constant ß 1 = Coefficient of variable X 1 X 1 = Independent Variables E = Error Term BINARY

STAGE 1: OBJECTIVES OF LOGISTIC REGRESSION ,[object Object],[object Object],DECISION PROCESS

STAGE 2: RESEARCH DESIGN FOR LOGISTIC REGRESSION

[object Object],[object Object],[object Object],[object Object]

4. SAMPLE SIZE ,[object Object],[object Object],[object Object],[object Object]

6. SAMPLE SIZE PER CATEGORY OF THE INDEPENDENT VARIABLE ,[object Object]

STAGE 3 ASSUMPTIONS ,[object Object],[object Object],[object Object]

STAGE 4: 1 . ESTIMATION OF LOGISTIC REGRESSION MODEL ASSESSING OVERALL FIT ,[object Object],[object Object]

3. TRANSFORMING THE DEPENDENT VARIABLE ,[object Object],[object Object]

WHAT IS P? p = probability (or proportion)

What is the p of success or failure? Failure Success Total 1 - p p (1 - p ) + p = 1

What is the p of success or failure? Failure Success Total 250 750 = 1000

What is the p of success or failure? Failure Success Total 250/1000 750/1000 = 1000/1000

What is the p of success? Failure Success Total .25 .75 1

What is the p of success? Failure Success Total .25 = 1 - p .75 = p 1 = (1 - p ) + p

WHAT ARE ODDS? ,[object Object],[object Object],[object Object],[object Object]

What are the odds of success? ,[object Object],[object Object],[object Object],Failure Success Total .25 = (1 - p ) .75 = p 1 = (1 - p ) + p

WHAT IS AN ODDS RATIO? ,[object Object],[object Object],[object Object]

HOW CAN WE COMPARE THE ODDS (Ω) OF MALES VERSUS FEMALES Group Failure Success Total A (Male) 182 368 550 B (Female) 75 375 450 250 750 1000

HOW CAN WE COMPARE THE ODDS (Ω) OF MALES VERSUS FEMALES Group Failure Success Total A (Male) 182/550 368/550 550/500 B (Female) 75/450 375/450 450/450 250 750 1000

HOW CAN WE COMPARE THE ODDS (Ω) OF MALES VERSUS FEMALES Group Failure Success Total A (Male) .33 .67 1 B (Female) .17 83 1 250 750 1000

HOW CAN WE COMPARE THE ODDS (Ω) OF MALES VERSUS FEMALES Group Failure Success Total A (Male) (1 - p A ) = .33 p A = .67 1 B (Female) (1 - p B ) = .17 p B = .83 1 250 750 1000

HOW CAN WE COMPARE THE ODDS (Ω) OF MALES VERSUS FEMALES ,[object Object],[object Object],Group Failure Success Total A (Male) (1 - p A ) = .33 p A = .67 1 B (Female) (1 - p B ) = .17 p B = .83 1

HOW CAN WE COMPARE THE ODDS (Ω) OF MALES VERSUS FEMALES ,[object Object],[object Object],Group Failure Success Total Male .33 .67 1 Female .17 .83 1

HOW CAN WE COMPARE THE ODDS (Ω) OF MALES VERSUS FEMALES ,[object Object],[object Object],[object Object],Group Failure Success Total Male .33 .67 1 Female .17 .83 1

[object Object],[object Object],[object Object],[object Object],How can we compare the odds (ω) of males versus females

4. ESTIMATING THE COEFFICIENTS ,[object Object],[object Object]

STAGE 5 INTERPRETATION OF THE RESULTS

It is calculating by taking by logarithm of the odd. Odd is less then 1.0 will have negative logit value ,odd ratios have a greater the 1.0 will have positive ,[object Object]

Compile logistic1 Idrees waris IUGC

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Andere mochten auch

Andere mochten auch (6)

Ähnlich wie Compile logistic1 Idrees waris IUGC

Ähnlich wie Compile logistic1 Idrees waris IUGC (20)

Mehr von Id'rees Waris

Mehr von Id'rees Waris (18)

Kürzlich hochgeladen

Kürzlich hochgeladen (20)

Compile logistic1 Idrees waris IUGC