How to write up a regression

Step one?
A 'type' of multiple linear regression was conducted to predict DV based on Ivs
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When is hierarchical regression useful?
if a theory is being tested then hierarchical should be used as it allows the researcher to validate the hypotheses used to determine the order of the predictors
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Why would stepwise not be used?
It would be greatly influenced by random variation and rarely given replicable results
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What is then presented?
Table of SD and mean and correlations
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1st Pre analysis check
Pre analysis checks were conduced before the study, which showed that non of the variables deviated from the mean
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Sample Size
For medium effect size: For multiple correlations: N>50+8*m
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For linear regression:
N>104*m
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For small effect size or skewed DV or measurement errors
N> (8/f2) + (M-1)
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For stepwise regression
n>40*M
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small effect size
0.02
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Medium effect size
0.15
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Large effect size
0.35
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singularity
There was no evidence of singularity (All tolerances greater than .1) or multicollinearity (All R's less than .9 and VIF
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What is singularity for?
We dont want to measure the same thing twice, singularities present mathematical difficulties
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Why is multicollinearity important?
3 potential problems: Untrustworthy, limits in the size of the variance and importance of predictors
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What happens if r is bigger than .9?
the compute correlations amongst IVs, remove appropriate IV
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Singularity is when a variable is?
Redundant (Combination of two or more other variables)
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Check if tolerance is?
1-SMC (SMC squared multiple correlation)
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Inferior to 0.2?
potential problem
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Inferior to 0.1?
Serious problem
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The case wise diagnostic showed?
Number outliers in the data, however Cooks distance was always less than one, maximum = ?
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Therefore?
they were not significant outliers and were not removed from the data
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Heteroscedasticity, normality
the histogram, the normal P-P Plot of regression standardized residuals, and the scatterplot shows normality of residuals, and show that there is no heteroscedasticity. Therefore, showing that the data doesn’t deviate from normality and used in MLR
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A significant regression equation was found with an...?
R2 = ... explaining ...% of the variance
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What does Adjusted R2 show?
Predictive power, adjusted R2 how much variance in the outcome would be accounted for if the model had been derived from the population rather from the sample, how well it generalises
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What would you write for a step wise regression?
SPSS searches for the best predictor and enters it into the model first. It will continue doing this until the predictor does no longer significantly improve the fit of the model, at which point it will reject the predictor and stop the process
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Stating ANOVA
A significant regression equation was found F(Df,DF)=..., p
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One unit increase in
IV corresponds to Beta units increase in DV.. All significant ones. This indicates that specify IVs all account for a significant amount of variance in the model
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Explain why the beta values are more informative than the b values?
’The beta value is a standardized value which represents the strength of the relationship between the DV and predictor variables.
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What does the B value represent?
the slope of the line between the DV and predictor variable, however it is not standardised and as such cant be compared between predictor variables
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Other cards in this set

Card 2

Front

When is hierarchical regression useful?

Back

if a theory is being tested then hierarchical should be used as it allows the researcher to validate the hypotheses used to determine the order of the predictors

Card 3

Front

Why would stepwise not be used?

Back

Preview of the front of card 3

Card 4

Front

What is then presented?

Back

Preview of the front of card 4

Card 5

Front

1st Pre analysis check

Back

Preview of the front of card 5
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