13. Assessing Relationships 3 Flashcards

1
Q

What does goodness of fit compare?

A
  • regression model

- mean

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2
Q

What does goodness of fit use?

A

SS_T, SS_R, SS_M

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3
Q

goodness of fit denoted by

A

R^2

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4
Q

What is R^2 a good gauge of?

A

size of relationship/prediction

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5
Q

What is also provided with a regression analysis?

A

f-stat

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6
Q

significant f-stat in a regression

A

means regression model is a good fit

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7
Q

f-stat and goodness of fit

A

measures how much the model has improved the prediction of the outcome compared to inaccuracy of the model

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8
Q

b_1 (slope) represents

A

change in outcome resulting from a unit of change in the predictor

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9
Q

if a regression coefficient is 0:

A
  • unit of change in the predictor variable results in no change in predicted outcome
  • regression line is flat
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10
Q

What is used to test the null hypothesis that the value of b is 0

A

t-stat

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11
Q

When is a multiple regression used?

A

when there are more than 1 continuous predictor variables (IVs)

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12
Q

steps to a multiple regression model

A

same as simple regression

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13
Q

methods of entering IVs for multiple regression

A
  • hierarchical
  • forced entry
  • stepwise
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14
Q
  • examiner decides order of entering predictors into model based on previous research
  • most important predictor entered first
A

hierarchical

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15
Q

all predictor variables entered simultaneously into the model

A

forced entry

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16
Q

divided into forward and backward

A

stepwise

17
Q
  • SPSS determines order of entry based on correlation

- highest correlation with the DV is first and only retained if it improves the model

A

forward stepwise

18
Q
  • all predictor variables entered into the model and the SPSS removes them one by one based on whether or not they improve the model
A

backward stepwise

19
Q

logistic regression

A

same as multiple regression except the outcome variable is categorical, not continuous

20
Q

types of logistic regression

A
  • binary

- multinomial

21
Q

binary logistic regression

A

only two categorical outcomes (DV is dichotomous)

22
Q

multinomial logistic regression

A

2+ categorical outcomes