search for: hypthesi

Hi all, I have dataset with 2 independent variable, one (x1) is continuous, the other (x2) is a categorical variable with 2 levels. The dependent variable (y) is continuous. When I run linear regression y~x1*x2, I found that the p value for the continuous independent variable x1 changes when different contrasts was used (helmert vs. treatment), while the p values for the categorical x2 and

...ing to act and increase a given output value by eg 30% (compared to not emplying this procedure). Now I have indepedent repeated measures (since the measures themselves are considered not very precise) for a (large) number of individuals with and without the treatment. Basically, I want to test the hypthesis that applying the procedure increases values in a linear way by a given factor, thus test the parameters of a linear regression (eg slope=1.3, offset may be different to 0). In extension to this, how could I make a confidence-interval for the estimated slop (due to the treatment) to check if the c...

Hello! I've run a simple linear model: result<-lm(DV~A+B+C,data=Data) My Data$A,Data$B, and Data$C are factors. So, lm automatically recoded them into dummy variables. I have all the results I need but one. Question: Where could I see the variance explained by all A dummy variables together, then all B dummy variables together, and all C dummy variables together - when other predictors