What do you mean by this?What test can I use? I have tried Multiple Linear Regression but the data doesn't pass any of the asssumptions.
And how large is your sample size?
With kind regards
K.
Hi, I'm going out of my mind...really need help.
I have one continuous dependent variable (test scores) and 6 categorical (with 2 categories - e.g. male/female) independent variables.
I want to look at the association/relationship between them or does the independent variables have an effect on the dependent.
What test can I use? I have tried Multiple Linear Regression but the data doesn't pass any of the asssumptions.
My deadline is so soon so please help..Thank you so much in advance
What do you mean by this?What test can I use? I have tried Multiple Linear Regression but the data doesn't pass any of the asssumptions.
And how large is your sample size?
With kind regards
K.
101lou (04-02-2014)
There are 68 participants.
I have tried multiple linear regression, i read their are 8 assumptions the data has to pass before you can run the test? linearity, normal distribution etc except their isn't a linear relationship between my dependent and independent variables or they are not normally distributed
initially i want to use chi square but the dependent variable would have to be categorical and mine is continuous (can't be categorised)
any help please?
You said you had 6 binary variables, so the bivariatetheir isn't a linear relationship between my dependent and independent variables
relationships cannot be non-linear.I am not sure what you mean by this. You haveor they are not normally distributed
to check the residuals of the multiple regression;
the residuals should be from a normal population
(but with n > 50 departures from this are not
cosidered serious).
With kind regards
K.
101lou (04-03-2014)
OK thanks! So I am doing the right test by doing Multiple Linear Regression?
I assume you used dummy independent variables. Ordinal independent dvariables are I believe always linear and I assume this includes dummies. Why do you conclude they are not linear?
"Very few theories have been abandoned because they were found to be invalid on the basis of empirical evidence...." Spanos, 1995
Noetsi can you clarify your last answer, I have run into this problem as well. I was always told that the relationship between the Dependent variable and the independent variable had to be linear... If you have a dummy variable (say male =1 female=0) then by definition you are comparing groups and the variable are not linearly correlated). it is therefore assumed that since dummy variables basically split the data into groups, they are linerally related to the dependent variable?
On a related question, does the Independent variable have to be normally distributed related to the dependent variable? meaning if one variable was age and another was income, what if income was FAR more variable at young ages than it is at old ages (it is). SO what is you have heteroscetastic data in a scatter plot of Age vs Income? Does that matter, or is it only the normal assumption of the residuals that matter?
Thanks so much!
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