Multiple Regression

?
  • Created by: ava234
  • Created on: 09-05-22 09:24
What is a regression?
examines if we can estimate the value of an outcome variable on the basis of the predictor variable
1 of 23
What is a multiple regression?
An extension of a multiple regression where there is more than one predictor variable.
2 of 23
Forced entry MR
Predictors are based on previous research.
No particular order of entering variables.
Variables are forced into the model.
3 of 23
Hierarchical MR
Predictors are based on previous research.
Researcher decides the order of entry - goes from known predictors to new predictors.
4 of 23
Stepwise MR
based on maths.
computer select the best predictor and that get entered first.
can be forward (as above) and backward.
5 of 23
Key parts for analysis
The regression line
R2 value
Intercepts
Betas
6 of 23
9 Assumptions of a MR are...
Sample size
Variable types
Non-zero variance
Independence
Linerarity
No perfect multicollinearity
Homoscediasticity
Independent errors
Normally distributed errors.
7 of 23
Sample size ...
for every 1 predictor, there should be at least 10 participants, but the more the better.
8 of 23
variable types
Predictors = quantatitve (Categorical/ordinal)
Outcomes = quantatitve (continuous/unbounded)
9 of 23
non zero variance
predictor variables should not have a variance of zero
10 of 23
independence
all outcome variables should be independent
11 of 23
linearity
relationship between predictors and outcomes is linear
12 of 23
No perfect multicollinearity
correlation between predictor variables cannot be too strong
13 of 23
homoscediasticity
at each level of predictor variable, the residual terms should be constant
14 of 23
independent errors
for any two data points the residual points should not correlate
15 of 23
Normally distributed errors
residual values are random and normally distributed.
16 of 23
How to check assumptions
**- calculate in advance
VT- check measurements
NZV- check by calcluating SD of variables
I- outcomes scores all from different people
L- SP**
NPM- check VIF
H-SP**
IE- durbin watsin
NDE- SP**
17 of 23
VIF stands for...
Variance Inflation Factor
18 of 23
Results of VIF mean...
VIF> 1 = biased regression
VIF> 10 = definately a problem
19 of 23
results of tolerance ...
Below 0.1 = serious problem
below 0.2 = potential problem
20 of 23
Durbin watson test
tests correlations across error terms
21 of 23
Durbin watson values mean...
2 = UNCORRELATED
>2 = POSITIVE CORRELATION
<2 = NEGATIVE CORRELATION
>3/ <1 = DEFINATE PROBLEM
22 of 23
Steps to MR
1. Descriptive statistics
2. Regression
3 reject or fail to reject
23 of 23

Other cards in this set

Card 2

Front

What is a multiple regression?

Back

An extension of a multiple regression where there is more than one predictor variable.

Card 3

Front

Forced entry MR

Back

Preview of the front of card 3

Card 4

Front

Hierarchical MR

Back

Preview of the front of card 4

Card 5

Front

Stepwise MR

Back

Preview of the front of card 5
View more cards

Comments

No comments have yet been made

Similar Psychology resources:

See all Psychology resources »See all RM resources »