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Questions tagged [regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

3 votes
1 answer
89 views

How should I handle a mass-point in the dependent variable when running OLS regression in R? I’m working with a a household expenditure dataset (Living Costs 2019) where the dependent variable is the ...
Jim's user avatar
  • 31
0 votes
0 answers
10 views

i am an undergraduate student working on an empirical project about the effect of FDI inflows on GVC integration in Egypt, using annual data from 1995–2023 (29 observations). My dependent variable is ...
Omar Akram's user avatar
0 votes
0 answers
36 views

In our questionnaire the answers are in the categorical format therefore we used dummy trapping for the regression part, however we have a doubt to use which of the following 2 ways: (i) For models ...
Gayuth Waidyaratne's user avatar
6 votes
3 answers
466 views

The outcome variable of my study is the level of knowledge of tobacco cessation services, with three categories: no, low, and moderate/high. The sample size is 660, but some predictors have cell ...
Md. Golam Kibria's user avatar
2 votes
1 answer
115 views

I’m trying to use the R poly() function with degree 1 to force glm to interpret a factor linearly. I’m puzzled by the fact that the size of the sample seems to increase the coefficient of the ...
Guillaume's user avatar
0 votes
0 answers
17 views

Consider the simple linear regression model with the following assumptions: I am trying to verify that $\dfrac{\hat{B}_1 - B_1}{\sigma / \sqrt{\sum_{i=1}^n (X_i - \bar{X})^2}} \;\Big|\; X_1,\ldots,...
secretrevaler's user avatar
1 vote
0 answers
59 views

I am going through the creation of a prediction interval for a value drawn from the conditional distribution of $Y$ given $X=x$ under simple linear regression as shown in the image above. The ...
froot's user avatar
  • 83
1 vote
0 answers
65 views

I am trying to find the uncertainty/error in the slope of a linear regression of a data set where the data contain standard errors. However, searching for this online is very confusing as there are ...
Michael Henchard's user avatar
0 votes
0 answers
36 views

I am trying to perform a Monte-Carlo simulation on quantile regression using R. Currently I am getting stuck simulating the data from the model below. ...
UNI39's user avatar
  • 11
3 votes
2 answers
116 views

I want to do a regression analysis after a GMM. I have a dependent variable with three categories (classes), which differ in their posterior probabilities. That's why I included the posterior ...
liz.stat's user avatar
6 votes
3 answers
178 views

I’m modeling mortality using a multivariate logistic regression model with a nonlinear effect of X1 and I’m examining whether this relationship changes across ...
Konstantinos Gkirgkiris's user avatar
0 votes
0 answers
16 views

I am using gradient boosting regressor from scikit-learn with squared error as the loss function. Then i want to plot the training set vs test set curve. Based on what i read, it is used to see the ...
Ocean's user avatar
  • 11
0 votes
1 answer
60 views

I am attempting to understand how each independent variable effects the probability of each dependent variable, which are ordinal (0, 1 and 2). Therefore, I am attempting to use ordinal logistic ...
92carmnad's user avatar
0 votes
0 answers
44 views

Suppose I was given a data set, say, golf, in the form of an MLR model. Given that best subset selection is choosing the top 5 best models of each size, how would ...
DavyJonessss's user avatar
4 votes
4 answers
331 views

I’m working on a logistic regression model where I want to examine whether the effect of one continuous predictor (X1) on a binary outcome depends on another ...
Konstantinos Gkirgkiris's user avatar

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