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

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5 views

Back-transformation of Yeo-Johnson transformation in R [on hold]

I'm studying linear regression models. I want to compare the performance of regression model before and after data transformation. I transformed my data because it does not hold the linear ...
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0answers
17 views

Proportion of variance explained, prediction accuracy, and noisy criterion variables

A given criterion measure is corrupted by noise such that only 60% of its variance is attributable to a true signal. This noisy measure of outcome is regressed against some number of predictors and a ...
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1answer
45 views

regression sum of squares in multiple linear regression

I'm looking for some help with the following practice question for an upcoming midterm:
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16 views

Regression with some observations having more than one factor level

I have data I want to analyze using multiple regression or machine learning: the response is cells for which I measured viability (a continuous response) and the independent variables are the genes in ...
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1answer
14 views

Is alpha error inflation a problem with multiple ordered logistic regressions?

Following problem: I'm doing a survey where my independent variables are: (1) the perceived attractiveness of a product on a 7-Likert-scale and (2) the willingness to invest in such a product as a ...
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0answers
13 views

What's the difference between t-test and sequential F-test?

I just started learning linear regression, and I couldn't completely understand the difference. I know the t-test is testing NH:$\beta_i = 0$ and AH: $\beta_i \neq 0$. The overall F-test is testing ...
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17 views

Confidence and Prediction Intervals for Multiple Linear Regression Model

I am looking for a derivation of confidence and prediction intervals for a multiple linear regression model. I have seen that for a given vector of predictors $(x^*)$ and $X$ denoting the design ...
8
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1answer
88 views

The proof of shrinking coefficients using ridge regression through “spectral decomposition”

I have understood how ridge regression shrinks coefficients towards zero geometrically. Moreover I know how to prove that in the special "Orthonormal Case," but I am confused how that works in the ...
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0answers
12 views

Should I include the level variables along with the difference variables in the Error Correctional Model(ECM)?

I am running an ARDL model, I have both levels and difference variables. I know for sure that the difference variables should be included in the ECM but should I include the level variables as well?
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0answers
10 views

Is it wrong to mix up the data categories in a multiple regression (first difference, levels, logs, dichotomous)?

I would like to estimate a fixed effects model with my panel data. My dependent variable is a standardized first difference. My independent variables are: standardized variable in levels (...
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1answer
21 views

Timeseries with binary regressors

I'm trying to identify impact of some causal events on a given timeseries. However, the trouble is I only know whether the event occurred or not (binary). What kind of techniques can I use to create ...
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0answers
14 views

What is the best analysis to do to test for a correlation between 3 different variables?

I have 3 likert scales which I have put together into a survey to about 60 participants. I would like to investigate their relationship. I know I am looking at correlation - and think that multiple ...
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1answer
41 views

Hypothesis testing with quotient of regression coefficients

Suppose we have the following multiple logistic regression model $\beta_0 + \beta_1 X_1 + \beta_2 X_2$, where $X_1$ and $X_2$ are binary variables, and $\theta = \beta_1 / \beta_2$. Then I have two ...
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1answer
37 views

Does AUC for multiple logistic regression make sense if prediction is not the goal?

Does it makes sense to calculate the AUC if I do not want to use my multiple logistic regression model for predictions? I only want to calculate some odds ratios and test if the variables in my model ...
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0answers
27 views

Regression analysis method when data is linked to a normalised time… and only hold a relationship for some of it

Stats novice... Please be patient, but I would really appreciate some help. I am using SPSS. I have made some kinematic measurements of a closed chain, repeated movement. I have a large number of ...
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0answers
31 views

How to manually calculate dffits?

I am trying to replicate what the function dffits() does in R. I need it for a school project. Can anyone help me? Sorry, if this is the wrong place to ask.
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1answer
65 views

Change regression model ($x^*_i = x_i -10$)

I am solving an exercise on multiple linear regression. Near the end I will be asked for the same data as the previous model, it is the maximum likelihood estimates. The previous model: I have ...
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2answers
45 views

Is it possible to run multiple logistic regression for small sample size?

I have collected data, there are 300 non-injury and only 17 injury. Four categorical variables are significant according to Chi-squire, then I used Multiple logistic regression for significant ...
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21 views

How to use LassoCV to obtain most informative independent variables by setting weights of others to zero [closed]

I want to use the lassoCV function from scikit package. In total I've 8000 data. All of these 8000 points have labels. Up to today, I've always used 3 seperated ...
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1answer
13 views

Performing variance inflation factor with R [closed]

Am working with R and I want to use the vif function to perform multicollinearity test but then any time I run what I get is "Error:could not find the function "vif"". I need help around this problem.
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0answers
11 views

multiple regression graph maker [closed]

I am searching for some online program (website / app) that creates multiple regression graph from values which the user fills, anyone familiar with one? (using some statistical program is ...
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1answer
24 views

How could I determine the most important smallest subset of my independent variables in multivariable linear regression [closed]

First of all I have to say that, My knowledge about statistics limited. I'm trying to learn the topic currently. I have a high dimensional data. Formally: I have 7000 points in which all ...
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0answers
16 views

Purging dynamics in multiple regression (cointegration)

I was reading Bewley and Yang method to purge dynamics of a multiple regression method as explained towards end of page 4 in this paper. The authors basically state that to remove dynamics from a ...
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1answer
45 views

Does the order of entering predictors in multiple regression model change the standardised Beta coefficients?

I am reviewing a number of research papers regarding domestic space heating energy consumption which used multiple regression techniques to identify the main determinants of space heating in the ...
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1answer
30 views

Standard error of residuals v.s. standard error of regression

We know that in simple linear regression the variance of the regression error, $\sigma^2$, is estimated by $\frac {\sum_{i=1}^{n} (y_i - \hat y)^2} {n-2}$, i.e., the Mean Squared Error of the errors. ...
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18 views

Consolidation of items for regression analysis & inter-construct correlation analysis

I am a stats newbie and have a very basic question. Please forgive me if the question may seem too foolish. I wanted to conduct a regression analysis between the 2 variables, USE (dependent) and ...
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0answers
11 views

Panel Data - random effect regression - evaluation of the model

I would like to know how to evaluate a random effects regression (multilevel model). Let's say, a model with two levels (trials, level 1, nested within participants, level 2) returns these values: R-...
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26 views

What is it that you're doing when you do a single t test on one predictor of a multiple regression model?

I hope my interpretation is correct. When you're doing a t-test on a single predictor of a multiple regression model, are you looking at how it behaves while the other coefficients are fixed?
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7 views

Method for a continuous variable for each sub-level of an ordinal variable?

I have three variables. A dependent variable (y) which is continuous, one dependent variable that is ordinal (x1), and one continuous variable which is bound (between 0 and 1, x2). I would like to ...
3
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1answer
245 views

Regression when response variable is a function

I have a set of data $(X_i,Y_i)$, $i=1,\ldots,n$ where $X$ and $Y$ are supposed to satisfy the following equation $$ y = \beta_0(1+x^2)^{\beta_1},\quad x>0, \quad\quad (1) $$ I am interested in ...
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28 views

What regression to use when dependent variable has cutoffs? [duplicate]

Suppose that my dependent variable has hard cutoffs in the sense that it is physically impossible to obtain values outside of a certain range. (If it matters, the dependent variable is a percentage ...
2
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2answers
21 views

Question on Interaction terms with a dummy variable

I have the following model. Sales = B0 + B1.Age + B2.Mobile where Mobile is a dummy variable that has the value of 1 if mobile, and 0 otherwise. Age is a ...
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10answers
3k views

What are some of the most common misconceptions about linear regression?

I'm curious, for those of you who have extensive experience collaborating with other researchers, what are some of the most common misconceptions about linear regression that you encounter? I think ...
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19 views

How can one measure the R-squared of a PLS regression model's Test set in MATLAB?

I was following this tutorial for PLS regression in MATLAB. They show how to choose the number of components for the model, but the yfit that they calculate, refers to the training set of the model if ...
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0answers
12 views

Control for multiple comparisons in an exploratory study?

I have an exploratory study where I investigate the relationship between several predictor variables (>10) and a few outcome variables (4). The large number of variables is not random but conceptually ...
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33 views

Multivariable Regression on correlated / collinear variables

Let us consider a variable $Y$ on which we want to apply a multivariable linear regression on the variables $X_1$ and $X_2$. $X_1$ and $X_2$ are collinear by construction, with $X_1=ab$ and $X_2=bc$, ...
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1answer
31 views

What are the alternatives to MMRE, PRED and MdMRE for validation?

I am working over the statistical validation of data. Till now I have computed MMRE, PRED and MdMRE. But I need alternatives to these because MRE is sensitive to data with large MRE's.
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35 views

Does Raising Independent variable to a power in Linear regression have any impact on model ?

I have a linear model in R, equation is below lmmodel31 <- lm(log(ExpensePerMember) ~log(IncomePerMember) + BranchCluster + log(TotalMember) +RentCluster + FoodCluster+IncomePerMember*...
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11 views

Estimate parameter of correlated regressors using two-step regression

Consider the following "true" multiple regression model (observation index omitted for simplicity): $$ Y = \alpha_{1} + \alpha_{2}X + \alpha_{3}Z + u $$ where $u$ is white noise, normally ...
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37 views

Why the coefficient of regressors in robust multiple regression is beyond 1 even though I have normalized the data

Could you please help me with my confusion: I have used the robust multiple regression model(both X and y have been normalized by using zscore) and want to get the beta(standard coefficient of the two ...
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2answers
49 views

Why should we not perform linear regression to predict ordinal dependent variables?

I am reading An Introduction to Statistical Learning. In this book, section 4.2, page 130 (text given below) mentions that linear regression would not be useful to predict ordinal variables because ...
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16 views

Define a model using logistic regression

I am new at scorecard development and I use SPSS for running the statistics necessary in the process. I in the step of the logistic regression part for 37 variables using stepwise regression. I get in ...
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1answer
21 views

anova() for model comparision _ Regression

let's suppose; I am fitting some models to a data set: ...
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2answers
28 views

Multicolinearity Test for Multiple Multivariate Regression

I have multiple independent variables and multiple dependent variables, some categorical and some quantitative. I have created a data sheet with dummy columns appropriate to each categorical variable. ...
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1answer
6 views

How to verify linear functional form in a MLRM?

Im prforming a Linear regression but i don't know how to verify that the coefficients are linear (Performing with Gretl software) could you guys help me to find a way to verfy this? Thanks in advance!...
0
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1answer
24 views

Standard Error for a Parameter in Ordinary Least Squares [duplicate]

I am studying parameters generated by the method of Ordinary Least Squares, in particular, a parameter's associated standard error. Wikipedia suggests calculating $$s^2=\frac{S\left(\hat\beta\right)}...
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0answers
10 views

A Game Plan for Cross-Section Modelling

Imagine we have already built our linear regression model, with a certain dataset. Which order of tests would you follow to be sure that whatever conclusions you may want to extract are correct? For ...
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20 views

Specify a mixed effect model for per patient treatment effect and interactors for such effect

I have a study design setting where each patient received a treatment and was assed again after 30 days. the dependent variables are a set of symptoms and clinical values. I thought of a design where ...
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31 views

regression model interpretation [closed]

Housing starts = 50 - 7 Mortgage rate + 7 Q1 + 9 Q2 + 7 Q3 Adjusted R²: 0.74 All variables significants is ...