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

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Multiple test correction procedures for multiple regression with dependent predictors

A researcher is employing OLS multiple regression to examine the independent effects (i.e., partial correlations) of a moderate (~8) number of theoretically-relevant predictors on some outcome. The ...
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12 views

Is Multiple Regression the right choice for my statistical design?

I am studying the relationship between mental health offices and judgments of perceived care expected within those environments. Participants will rate different photographs of mental health offices ...
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3answers
67 views

Is time in linear regression a categorical or continuous variable?

I am try to perform multiple regression. One of the feature variable is time of the day represented by 0 to 23. I am confused whether I need to used dummy coding or not. Is this a categorical variable ...
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10 views

Pointwise Confidence and Prediction Intervals with LMER {lme4}

I am trying to return the pointwise confidence and prediction intervals for a linear-mixed effects model using random intercept and slope, but I'm getting errors in my code. ...
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3answers
59 views

Question on Residuals

After generating the regression model in R using lm, the results will be passed to summary function. results <- lm(y~x, data) summary(results) This function ...
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15 views

Relationship: Regression Coeffecient and Line Plot Trendline Slope

Why does the slope of my line fit plot not match the coefficient of the same variable in my regression? For one of the variables, the coefficient is positive while the line fit plots trendline is ...
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1answer
23 views

How to deal with different outcomes between pairwise correlations and multiple regression

I have different results from a correlation table and a multiple regression model. I know that it is an effect of multicollinearity because correlations up to $.474$ exist between predictors, but this ...
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7 views

When nesting within two factors must the GLM contain their interaction?

I am running a general linear model with repeated measures - individual is a random factor, which should be nested within both treatment and family (also random). In the past, my statistics package ...
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14 views

How to choose variables to include in ANCOVA

I have a data set that includes a DV (Richness or Abundance) and multiple continuous and categorical variables: ...
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1answer
18 views

Do models with multiple covariates and single covariate models differ from each other?

I have a binary response variable with 9 predictor variables. Lets denote the predictors $A, B, C, D, E...$ Suppose I run a model $y_i = \beta_0 + \beta_1 A + \beta_2 B + \beta_3 C + \cdots$. The ...
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1answer
45 views

Linear regression with sine/cosine elements

How can you derive formula and regression coefficients for a regression model of a form $y(x)= A + B\, x + C\, \cos (2 \pi x) + D\, \sin (2 \pi x)$? I know that there are automatic tools who can do ...
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1answer
23 views

Whether to apply the logit transformation to proportional predictor variables in a multiple linear regression? [including proportions of 0.0%]

In a linear regression, I have a number of predictors variables that are expressed as proportions. The outcome variable is continuous. My residuals are not normally distributed, with a mild to ...
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16 views

Need advice on unbalanced time-series dataset, for use with CAPM regression

I have 40 years of monthly historical returns of around 3000 mutual funds. The dataset contains both active and inactive funds, so some funds have data for the whole period, whereas others will have ...
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18 views

Structural Break - Stata

I have used Stata to run a time series multiple regression. I know that there is in fact a structural break in the data and the point at which it occurs; therefore, I have estimated the regression ...
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2answers
89 views

What to do if residuals are not normally distributed?

I was wondering what to do with the following non-normal distribution of residuals of my multiple regression. Normality test of standardized residual ...
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1answer
53 views

Does one need to transform percentages/proportions for a multiple linear regression?

I am aware that one should transform percentages and proportions when using them in an ANOVA, due to the values being bounded by 0 and 1. I have seen suggestions that the best transformations are ...
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33 views

Statistical technique to apply in Airline Industry [closed]

I am working to Airline Industry data where frequency of travelers in a year is up to 1. I need to increase the frequency of the travelers using some predictive modelling approach so that campaign ...
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0answers
17 views

How large should the sample be to start using batch gradient descent versus normal equation

Suppose you want to train a multivariate linear regression on an n x m dataset. The runtime of determining your parameter theta = (theta0, theta1, ..., thetam) using the normal equations is ~ O(m^3), ...
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1answer
33 views

fixing the intercept in multiple regression

I am interested in using OLS regression to model the relationship between two predictors (X1 and X2) and a response variable (Y). However, for theoretical reasons I know that when X1 = 0, Y must also ...
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2answers
112 views

Bayesian logit model - intuitive explanation?

I must confess that I previously haven't heard of that term in any of my classes, undergrad or grad. What does it mean for a logistic regression to be Bayesian? I'm looking for an explanation with a ...
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1answer
36 views

How can I check whether multicolinearity exist between categorical variables or numerical and categorical variables?

I did a linear regression with 10 variables, including categorical and numeric variables. But although my $R^2$ was 0.8 there were only 2 variables that were statistically significant. Am I correct ...
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1answer
15 views

Interpretation of “Same Slope” in Multilevel Modeling Example

An example of multilevel modeling : Consider an educational study with data from students in many schools,predicting in each school the students’ grades y on a standardized test given their scores on ...
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1answer
62 views

Multiple regresssion K-S test in R

As suggested, this question first appeared on SO but was now merged across to CV So we can run a K-S test to assess if we have a difference in the distribution of two datasets, as outlined here. So ...
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1answer
60 views

Appropriate reasons to exclude independent variables from regression

I am running a series of hierarchical regressions with a lot of independent variables. All the IVs show a loose theoretical relationship to the DV. My supervisor has suggested excluding IVs from ...
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13 views

scaling coefficients in a regression

this might be a relatively beginner question: Using a multiple regression, say I was testing the explanatory power of a model that had a normal coefficient but also a scaling coefficient based on ...
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1answer
19 views

What is the meaning of Confidence Intervals regarding Hold Out samples?

Let's say you have a regression model that estimates GDP. Your model has a Standard Error of 1%. So, you can readily build Confidence Intervals around your regressed estimates. Your 95% CI will be ...
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1answer
19 views

Linear regression with interaction SPSS

I have to run a linear regression analysis with an interaction effect of two categorical variables: Modality (audio, visual and audio-visual) Repetition (1x, 2x and 4x) I have already dummified ...
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1answer
37 views

X and Y are uncorrelated, but X becomes significant when X*A is included in model

At the zero-order level, X is not correlated with Y. When I add X and A into a regression analysis to predict Y, only A is a significant predictor. A itself is correlated highly with Y at zero-order. ...
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1answer
52 views

If x2 & x3 affect x1, & x1 affects y, should x2 & x3 be included in a regression model?

Let's consider the regression $y=x_1+x_2+x_3+\varepsilon$ It is known that $x_2$ and $x_3$ affect $x_1$, but $x_2$ and $x_3$ do not affect $y$. $x_1$ can affect $y$, but only to a small extent. The ...
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1answer
35 views

Logistic regression or OLS regression?

I am a trainee clinical psychologist investigating whether age, ethnicity, or gender influence the uptake of Cognitive Behavioral Therapy (CBT) for psychosis in four different complex needs teams. ...
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45 views

What statistical approach to use for this kind of analysis?

I have 1 dependent (continuous) variable, 3 explanatory (continuous) variables and a bunch of control variables. The explanatory variables are my interest variables.I want to do a categorical ...
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24 views

Why conduct large scale multiple comparisons rather than multiple regression?

Is there ever a compelling reason to conduct multiple hypothesis tests versus a multiple regression when comparing a response in two treatment groups among many (possibly thousands or millions) ...
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27 views

Multiple Logistic Regression power analysis

So I have a logistic regression model and output an R² value. I then go and add another predictor variable to a second model. I can output a new R² value associated with the second model. When I run ...
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0answers
24 views

Regression model estimates vary depending on method of regression selected (stepwise/enter) with same predictor variables (SPSS)?

I am building a model for prediction with around 15 independent and one dependent variable. If I run a stepwise model (I understand the disadvantages of doing this) on the data, I get a set of ...
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23 views

How do “stacked” repeated samples influence our rules of thumb for minimum samples size in regression?

A professor in one of my graduate statistics courses once said, when briefly reviewing simple linear regression: "I would never EVER fit a line to fewer than 8-10 data points, it would make me ...
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66 views

R syntax - Multivariate regression with an unknown coefficient or two, for a dummy (engineer)

Something I rather vaguely asked a few months back, saw the tumbleweed roll by (actually hacked some hardware in the time, to get a few answers) before the question was deleted, so I'll try again on a ...
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15 views

How can I filter marketing campaigns out of my decomposed seasonal data?

I've recently jumped into the deep end of statistical analysis of revenue. I've learned a ton about statistics, probability, decomposition (stl), and the Python and R languages. I feel like I'm ...
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266 views

Reviewer questioning my stats, need a second opinion (multiple linear regression)

I just got reviews for my first article and one of the reviewer is questioning my stats and he made me doubt about it. I cross-posted on reddit and one redditor suggested me to come here for a second ...
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24 views

How to partition $R^2$ among predictors in multiple regression with interaction terms in R

Say I have some predictors, and I know how they affect some dependent variable: ...
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22 views

Eview's result interpretation

I've used Eviews to estimate a variable based on some independent variables. although R^2 is high, t-statistics are very low (for c(2) and c(3) is 0.0004) what it means? should I remove variables by ...
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28 views

Paired Hypothesis Test in TWO Linear Regressions

I am wondering how to perform a paired hypothesis test in a panel regression. I have been looking in many stats books but I have not found anything. The question goes: assume for $i=1,2,\cdots, N$ ...
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15 views

Relative Importance v.s. Magnitude of Coefficients

My project tries to find "similar public schools" for a set of charter schools using school level data. Current method gives different weights to several key school-level variables(% Special Ed, % ...
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27 views

How to use Likert Scale data in regression analysis?

My knowledge about statistics is elementary and I would really appreciate some help or suggestions in solving my current problem. I am doing a dissertation and I will collect the data using a likert ...
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0answers
36 views

Applying logit transformation to the predictor variables in multiple linear regression [closed]

I want to do multiple linear regression (Not a logistic regression) with continuous response, and a mixed of continuous and categorical variables in the predictors / regressors. I know that we can do ...
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0answers
31 views

Building a Predictive Model

I'm inexperienced and confused in statistics, so I need help. I have a data table, values are temperature, particulate matter(PM), and vegetation indexes. And idea is that when PM increases, ...
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2answers
51 views

Can I include two predictors (A & B) in one regression model if predictor A is dependent on B?

I want to include two predictors (total brain volume and corrected gray matter volume) into one regression model in order to predict the level of cognition (dependent variable). However, this ...
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1answer
7 views

Unable to predict using bart() {BayesTree}

I used bart function from BayesTree library to build a model on my training data. It fits my training data very well. However, I'm unable to predict for the test set and check its performance. ...
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2answers
77 views

Better Quantitative Measure of Predictor “Relevance” than p-values?

I have a regression of the general form: $$ Y = \alpha + \beta_{1}*X_{1} + \beta_{2}*X_{2} +\beta_{3}*X_{3} + ... + \epsilon $$ Let's assume the following constraints: k=14; all X's are ...
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Biostatistics: testing for differences in protein composition in two tissues measured longitudinally

Thank you for your help! I am confounded. I am trying to analyze experimental research data that looks like this: Dependent variable (DV) components: Two populations of cells (GFP and LacZ). Each ...