Linked Questions

7
votes
2answers
13k views

Significance of dummy variables in regression

I am using categorical variable (having three categories) as independent variable in model and found that one category is coming to be significant while another category is not coming to be ...
6
votes
2answers
7k views

In a multiple linear regression model, how do I test the null hypothesis that multiple coefficients are equal to zero simultaneously?

For example, if I have Y = b0 + b1X1 + b2X2 + b3X3 + b4X4, I want to test H0: b1 = b3 = 0, at alpha = 0.05. I ran an lm model ...
6
votes
2answers
4k views

Dummy variables in multiple regression, why use an intercept?

When performing a multiple regression with dummy variables, is it really necessary to include an intercept term in the design matrix? By dummy variables, I mean indicator variables; a one in the ...
5
votes
2answers
409 views

Testing significant differences between regressions in R

I am running several phylogenetic least squares analyses in R, where I'm taking an existing data set for several species, and adding two new species for which I have data. I want to do is test whether ...
5
votes
2answers
8k views

Calculate F-statistic / p-value for subset of co-efficients in R

I'm wondering if there's an easy way of calculating an F-statistic / p-value for a subset of model coefficients. Particularly in R? I'm not sure what test would be needed to calculate this. For ...
3
votes
2answers
7k views

How to interpret insignificant categorical variables for logistic regression

I am trying to interpret categorical variables with more than two classes. Some are significant whilst other classes are not. What can I infer from the insignificant ones? Does this mean the ...
0
votes
2answers
7k views

Computing R-squared change, F-, and p-values for the interaction / moderation term [closed]

I would like to compute R-squared change for the interaction/moderation term in a multiple regression model, along with the corresponding F- and p-values. Previously, I have worked with the modprobe ...
7
votes
1answer
959 views

How to test whether linear models fit separately to two groups are better than a single model applied to both groups?

My question is how to tell if two regressions explain the data better than one. Let me be more concrete with an example (which I'm making up as I go, it's not meant to be plausible). Say I'm ...
3
votes
1answer
1k views

How can logistic regression have a factorial predictor and no intercept?

I tried a regression in the form ${\rm logit}(Y) = {\rm coefficient}\times X + 0 + e$, where $Y$ is a binomial variable and $X$ is a factor variable with $n$ levels. I noticed that removing the ...
2
votes
1answer
228 views

Modelling combined linear and quadratic age effects

I am running a GLM (Type III) with several predictors, including ${\rm age}$ and ${\rm age}^2$ as predictors. I am interested in knowing the combined effect size and p-value of ${\rm age}+{\rm age}^2$,...
2
votes
1answer
144 views

Explaining changes caused by dummy variables quantitatively

Consider the following linear model \begin{equation} Y_{j}=\beta_{1}+\beta_{2}E_{j}+\beta_{3}B_{j}+\epsilon_{j} \tag{*} \end{equation} where $Y_{j}$ represents the natural logarithm of the annual ...
2
votes
1answer
2k views

Partial F ratio from ANOVA table

In multiple regression, if you have just an ANOVA table, and nothing else, no specific data, how can you do a partial F test on X1, given X2 is already in the model? So, you have the ANOVA table: <...
1
vote
1answer
60 views

How to compare the regression coefficients of two independent variables between two groups

I want to test whether the coefficients of two independent variables ($x_1, x_2$) are different in two groups. I know I can use a dummy variable $d$ which equals $1$ for group $1$ and equals $0$ for ...
1
vote
1answer
293 views

Term is significant linearly, quadratically and in interaction?

I used deletion tests to identify ecological factors that relate to the number of parasites on rodents. There is one factor that is significant linearly, quadratically and in interaction. However, the ...
1
vote
1answer
4k views

Unique variance with regression analysis

I have some questions about unique variance and hope some of you can help. For instance, let say I have 3 predictors and 1 dependent variable (DV). I ran a regression analysis with a sequence of 3 ...

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