Regression that includes two or more non-constant independent variables.

learn more… | top users | synonyms (1)

0
votes
0answers
1 view

Multinomial logit model and Principal component analysis

I am trying to estimate if a household owns a PC, has access to PC or none. I have very large and rich dataset on household data. In the data set I don't have income variable so I was thinking to use ...
0
votes
0answers
10 views

Geometric interpretation of MLR

$\vec{y}=\mathbf{X_{n\times p}}\vec{\beta}+\vec{\epsilon}$ We know that $\hat{\beta}^{\text{LSE}}=(X^TX)^{-1}X^Ty$ If all the dimensions are orthogonal, we can obtain that $\beta_j=\frac{\langle ...
0
votes
0answers
6 views

Choose between models FE vs RE vs Pooled OLS

I have quarterly data for 3 countries for a period of 10 years. Number of observations = 123. I have the following two questions: I would like to know what tests should I perform to choose between ...
-4
votes
0answers
31 views

Best linear fit [duplicate]

Which one is the best fit according to these information? fit1 or fit2. I am NOT working with this in an academic context so explanations are not important to me.
2
votes
1answer
53 views

compare two linear models. Linear regression

I have made two linear regressions to estimate y and I get this results: One: ...
0
votes
2answers
23 views

Using a dichotomous categorical variable that has an underlying continuous dichotomy in a multiple regression?

FINAL EDIT I just found a good answer to this question in another thread in the forum here, therefore, I think this question could be closed. Thanks so much for your help and the clarification about ...
0
votes
0answers
9 views

which technique will be appropriate for my problem

suppose i have three independent variables x1 x2 x3 and one dependent variable y with following defination x1=test1 scores (20% of final score) x2=test2 scores (10% of final score x2=test3 scores (30% ...
3
votes
2answers
53 views

Does cross-validation on simple or multiple linear regression make sense?

Does it make sense to apply train-test split or k-fold cross-validation to a simple linear regression model or multiple linear regression model? I'm really confused about this because I saw this ...
0
votes
0answers
12 views

How to do multi-labelling regression in machine learning?

There are a few links available to do multi-label classification (not to be confused with multi-class). But how to do multi-label regression given a highly non-linear real-valued data set? My ...
0
votes
0answers
16 views

Vif and stepwise regression

I used the VIF to detect multicollinearity, I want to use forward selection and backward elimination procedures. My question is: Do I have to use all the variables in my dataset in the procedures or ...
1
vote
1answer
15 views

Regression with multiple dummy variables and dummy interactions

I have a model measuring Click through rates using 3 dummy variables. Placement location (PL1 vs. PL2) Ad type (Text vs. RM) Device type (Mob vs. Desk) Additionally I want to measure the ...
0
votes
0answers
13 views

Full conditionals for the parameters of a Bayesian regression with dependent components

Let $\mathbf{y}_i=\{y_{ij}\}_{j=1}^p$, $i=1,\dots ,n $ be a $p-variate$ vector and $$ y_{i,j} = \alpha_{j}+\beta_{j}x_{ij}+\epsilon_{ij}, $$ where $x_{ij}$s are known constants and ...
1
vote
1answer
38 views

LASSO regression when model is known

I am very new to regression as I have been reading "The Elements of Statistical Learning: Data Mining, Inference, and Prediction" by Hastie et al. on Standford's website this weekend. My goal is to ...
0
votes
0answers
11 views

Effect of number of variables on SSE of multiple linear regression model? [on hold]

Can adding new variables decrease the SSE for the model? Two models with the same dependent variables have some shared variables and some unique variables. Will the model having more variables have ...
0
votes
0answers
38 views

Constrained regression and lagged factors

I have a model that I need to estimate, where I've seen a similar example (Constrained Regression in R: coefficients positive, sum to 1 and non-zero intercept) but without the second part of ...
3
votes
0answers
20 views

What are the statistical properties of regression when a regressor is used as the dependent variable?

If you have a data generation process y=f(x)+ϵ and mistakenly regress x on y will your estimate be consistent for f inverse? Will your estimator be less efficient then if you had chosen to regress y ...
0
votes
0answers
9 views

how to calculate adjusted sum squares for each predictor in a multiple linear regression model?

I don't understand why the sum of adjusted sum squares of each predictor(0.0979+9.08723=9.1851) don't equal the total regression sum of square(11.7778)? And I know how to calculate sum of adjusted ...
0
votes
0answers
16 views

Linear model in R. Basics; how to read and understand the table [duplicate]

I am asked to fit a linear model for some data that my teacher has given. The first 5 lines of the R code is given by my teacher. X1 has 4 kind of outcome (1, 2, 3 and 4) and x2 has 6. I believe I ...
1
vote
1answer
48 views

Multiple regression in R results different to simple linear regression? [duplicate]

Hi I am having trouble acquiring the final results for presentation. The results from a multiple regression are different to my results in a simple linear regression. For example, the multiple ...
0
votes
0answers
11 views

what to do when proportional assumption is not met in stata

I have built a Cox multiple regression model. When I tested the proportional hazard assumption using estat phtest command, I realized the PH assumption is not met. In this case, what is the next step? ...
1
vote
0answers
3 views

Interpretation of diagonal detail for a 2D (Haar) Wavelet Transform

I am a statistics grad student, and I have just began exploring the topic of wavelet regression (specifically, Haar wavelets for discrete functions). I understand the generalization from a one ...
0
votes
0answers
5 views

Picking a particular model from regsubsets

I ran regsubsets in r from the 'leaps' library. I have gotten some 16 models in their order of which is best according to certain criterion. How do I select, say, model no.14 from this order and run ...
0
votes
0answers
7 views

Multiple regression with 5 continuous IVs and one continuous moderator in SPSS

I am trying to test a multiple regression model with 5 continuous independent variables and 1 continuous dependent variable. Also, I'm trying to test the moderating effect of 1 continuous variable on ...
0
votes
0answers
17 views

interpretation of CAPM test

the CAPM is the Capital Asset Pricing Model. If i test the null hyphotesis that all intercepts of a multiple regression (where the dipendent variable is a equity and the indipendent is the market ...
0
votes
0answers
15 views

Low variation in dependent variable

I want to study a setting where my dependent variable has quite low variation. Specifically the dependent variable in the regressions that I want to run, is a dummy variable which takes the value of 1 ...
3
votes
1answer
27 views

Test on SUR model

I have a SUR model with 22 equations, where each equation has the same 7 factors. I want to test if a coefficient (b3 in equation 1) is significantly different from another coefficient in another ...
3
votes
1answer
61 views

Data space, variable space, observation space, model space in linear regression

Suppose we have the data matrix $\mathbf{X}$, which is $n$-by-$p$, and the label vector $Y$, which is $n$-by-one. Here, each row of the matrix is an observation, and each column corresponds to a ...
0
votes
0answers
22 views

PROCESS macro in SPSS - Analysis for multiple IV?

I have a moderated mediation model with 4 IVs, 1 mediator, 1 moderator, and 1 DV. I can't find the right model in the templates provided by Andrew Hayes for his SPSS PROCESS macro. Can I carry out one ...
0
votes
1answer
29 views

p-values of the coefficients or AIC for model selection in multiple regression

I´ve got two models from a multiple linear regression (A and B, see below) and don´t know which to select. I want to predict a value called AW as good as possible, so I´d like to have the highest r². ...
1
vote
1answer
23 views

An independent variable in the logistic regression has 2.2%, 2.1% and 95.7% distribution [closed]

I have one independent variable in the logistic regression with a 2.2%, 2.1% and 95.7% distribution (three categories IV). My DV has good distribution (68% and 32%). How would this IV affect my ...
1
vote
0answers
20 views

Multiple regression - A question about dependent variable

I have a doubt about hierarchical regression analysis. My dependent variable is Presenteeism (the act of attending work while sick). Originally that variable has 4 levels (Has it happened to you ...
0
votes
0answers
20 views

Adding variables in multiple linear regression

Pretend that I had a MLR consisting of $Y=a+b$ and I wanted to add a new variable $c$ or $d$, but not both. So I would either end up with $Y=a+b+c$ or $Y=a+b+d$. I know I can run the regression on ...
0
votes
0answers
23 views

Dropping the non-significant parameters in multiple regression

Given the standard multiple linear regression model $$Y=X\beta+\epsilon\sim N(X\beta,\; \sigma^2I)$$ One derives the distribution for the estimated parameters $$\hat{\beta}\sim N(\beta,\; ...
0
votes
0answers
20 views

Smaller p-values on a selective multiple regression analysis [duplicate]

When I run a multiple regression analysis in Excel on 20 independent variables and 1 dependent variable (in two goes), I obtain in the summary a set of p-values. When I select the (six) ones that are ...
0
votes
0answers
13 views

Error measure in regression task by using a neural network

I am working on a regression task in which I which I want to predict vectors of about 30 values starting from textual documents using a Convolutional Neural Network. In particular, for each document ...
0
votes
0answers
9 views

Combine insights from linear regressions on multiple datasets with different outcome ranges

I have a number of datasets with the same (categorical) features/predictors and the same numerical outcome variable. I am studying the effect of each of these features on the outcome. The difference ...
0
votes
0answers
9 views

Imputation of predictors missing data for logistic modelling

I never used imputation of missing data and I would like to understand the effect of imputation in a specific scenario. Lets suppose that I have a dataset whit some predictors variable and one binary ...
0
votes
1answer
15 views

Hypothesis Testing Multiple regression with dummys and interaction

I have a model $$Y_i = \beta_{0} + \beta_{1} *P_i + \beta_{2}*B_i + \beta_{3}*E_i + \beta_{4}*B_i*E_i+u_i$$ where Y is a Rating, P is the price, E is the educationional level ( 0 no higher education; ...
1
vote
0answers
26 views

How to determine if a (binary) variable has a statistically significant effect on a response variable?

To be more specific, assume the following scenario: A customer advertising for a job on your site wants to know whether buying an extra ad-product or not will increase the number of applicants. You ...
0
votes
0answers
20 views

Why lower order term is necessary when higher order term is compulsory [duplicate]

I came across a result today stating that if the coefficient of the highest order of independent variable in the regression equation comes out to be necessary (via hypothesis testing), then the lower ...
0
votes
1answer
37 views

Is a mixed model including repeated measures is appropriate for me, and how to interpret it?

I have a repeated measures study including 370-ish people measured twice on all variables (var1 to var6, including exposure variable), with some subjects who didn't complete the second assessment yet ...
1
vote
0answers
16 views

Testing to Compare for “Impact” of Independent Variable on Dependent Variable

How can I perform a statistical test to judge impact of an independent variable on a dependent variable given multiple regression output? In the example below, how would I test if gender or work ...
1
vote
0answers
8 views

Testing the total impact of a predictor in a messy model

Suppose I have a regression model with several predictors ind interactions thereof. For concreteness, suppose we are studying a company's data on salaries and we have predictors ...
1
vote
2answers
43 views

Multiple regression with highly correlated variables

I have to do a multiple regression in order to predict the GDP, using some (or all) of the variables that I have (consumption, investment, govt expenditures, disposable income, price index, money ...
3
votes
1answer
134 views

ANOVA vs multiple linear regression? Why is ANOVA so commonly used in experimental studies?

ANOVA vs multiple linear regression? I understand that both of these methods seem to use the same statistical model. However under what circumstances should I use which method? What are the ...
1
vote
0answers
28 views

Is the intercept estimation affected by multicollinearity?

Suppose I am running a regression $$x_t = \alpha + b_1y_{1t} + \dots + b_m y_{mt} + \varepsilon_t$$ where the $y_{i}$ are potentially linearly correlated (Some have an IVF bigger than 4; generally ...
1
vote
1answer
24 views

How to determine if independent variables in multiple logistic regression model are independent or not?

I am trying a multiple logistic regression model. But I am suspicious that one of my independent variables is dependent on another. I wonder how to prove that the independent variables are truly ...
0
votes
1answer
22 views

High chi-square of the intercept in logistic regression

I run logistic regression models where the event rate is generally very low. In my models I get a large intercept term. What bothers me is the exceptionally high chi-square of the intercept term. How ...
0
votes
0answers
25 views

Adding a regressor to linear regression model that has nonlinear relationship with dependent variable

Let's say we have a linear regression model where Y is the dependent variable and X1 is the regressor. X1 and Y have a strong linear relationship. We want to add another regressor, X2. Turns out X2 ...
1
vote
1answer
33 views

Linear regression on choccake dataset

I am using faraway::choccake data, and I want to fit a linear model. I have used the following code: ...