# Questions tagged [regression]

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

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### Why do fixed effects in a logistic regression model differ depending on the presence of a random slope?

If I have two linear regression models, one with a random slope and one without (but otherwise identical), the fixed effects in the two models are identical. My understanding is that this stems from ...
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1 vote
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### Ordinal logistic regression with interaction

I have a dependent variable donation intention on a 7-point likert scale(1=totally disagree, 7= totally agree), an independent variable which is a dummy (0= price is not framed, 1 = price is framed) ...
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### Binomial regression with non traditional dataset

I am aiming to do a binomial regression, most aspects are close to textbook situations. But not on the datasets side, while I have a traditional dataset, that will split into training, test and ...
1 vote
33 views

### Identifying confounders in multiple linear regression

I am currently trying to identify confounders in a multiple linear regression, but I am a little unsure of a couple of steps. These are the steps I am taking: Check to see if the potential ...
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### R: emmeans back-transformation when using a constant value in the response formula

I am fitting a linear mixed model ...
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1 vote
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### Negative Binomial Regression with Moderation Effect

In H1, I predict the positive effect of a program on the consumer spendings. In H3, I want to predict the positive effect of a program on the number of referrals, while also predicting the positive ...
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1 vote
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### Ordinal Regression - Using a Continuous Attribute of 3 Categories as a Covariate as a Proxy for the Categories

I'm conducting an ordinal regression with SPSS 28. I have 3 subsets in my data (n=87 total, mostly equally distributed between the subsets) that represent 3 different scenarios where study ...
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1 vote
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### Assessing a single predictor with linear modelling [closed]

I have data that involves countries in and out of Europe, life expectancy, social support and expenditure per GDP. I want to assess how successful a single country in terms of life expectancy given ...
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### Should I normalize (preprocess/scale/log-transform) my data "before" imputing missing values with missRanger?

I am trying to impute missing values using missRanger package. missRanger is apparently much faster than missForest. I would like to know: 1 - Are these two packages any different in their imputation ...
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I am trying to estimate the coefficients $\lambda, \alpha, \beta_1, \beta_2, \gamma, \eta$ in the below equation using Python and some financial data $$\lambda \times \text{(participation %)} \times \... 3 votes 1 answer 26 views ### Features are Relevant for Regression but not necessarily for Classification - what to make of this? I have used the R Boruta package to check for feature relevance in predicting log returns of financial time series, the targets being the log returns themselves (for regression) and the sign of log ... • 4,574 1 vote 0 answers 23 views ### Lasso regression only predicts order of model correctly when poly() is set raw = TRUE? I'm looking at exercise 8 in chapter 6 of Introduction to Statistical Learning and have noticed that the ability of glmnet() to correctly identify the non-zero ... • 11 0 votes 0 answers 13 views ### Constructing a time dummy variable in DiD fixed effects model I am using a Diff-in-Diff regression design to evaluate the impact of a county-level tax hike (i.e. treatment variable) on tobacco sales (i.e. outcome variable) in a given county, relative to counties ... • 105 2 votes 1 answer 36 views ### Regression of a time series difference Suppose x(t) and y(t) are two time series. I regress y(t) against x(t), and obtain$$y(t)=ax(t)+b+z(t) $$for some regression constants a, b and residue z(t). Define \Delta u(t):=u(t+1)-u(... • 875 1 vote 1 answer 48 views ### Collinearity problem Consider a linear regression of this type: height: beta_0 + beta_1*weight. Adding BMI as parameter would add complexity to the problem or just cause a collinearity problem? 1 vote 0 answers 10 views ### The p value of my OPLS-DA model was -nan(ind), I don't know, what's mean, and the residual MS was infinite, I need help here? I obtained for the first time strange cross-validation results of my OPLS-DA model, the CV ANOVA was -nan(ind), SD residual was inf, MS residual was inf also, moreover, F test equal to zero. The ... 9 votes 1 answer 663 views ### What can be done about assumption violations in logistic regression? I am working on a logistic regression solution, and I'm experiencing some issues with assumptions according to the diagnostic graphs.For linear regression, I am familiar with addressing similar ... • 203 3 votes 1 answer 45 views ### When is least squares better than reduced major axis? Consider two linear regression methods: least squares regression (LSR) reduced major axis (RMA) I know the definitions of both regression methods but I would like to know when is the LSR better than ... • 31 1 vote 0 answers 18 views ### MAPE does not take into account the range of the output? I have a time-series regression model where the output is always in the range of 6000-6050. After training my model, I get a Mean Absolute Error of around 18 and hence, very low Mean Absolute ... • 11 0 votes 0 answers 21 views ### Using target values in both (X and y) arguments of fit(X, y) This question is based on SQL Server Machine Learning Services Ski Rental tutorial. We have a dataframe df: ... • 101 6 votes 1 answer 222 views ### Ridge or multiple linear regression following PCA? I have a real world clinical dataset with a severe issue of p >> n. I have thus decided to run PCA before modelling the data. This leads to a dataset with 150 samples with 85 features. I would ... • 185 0 votes 0 answers 7 views ### Level 3 variance increase when adding a contextual predictor? I am conducting a multilevel regression analysis on a survey dataset that has three levels: Individuals - Country-Years- Country. I am regressing a series of time varying and time invariant ... 0 votes 0 answers 28 views ### How to prove change in a time series when the population is growing? I have a small dataset with data on the number of heart and liver donors from deceased patients each year (from 2012 to 2021). I would like to find out if there has been a change in the number of ... • 45 0 votes 0 answers 8 views ### Sufficient conditions for equivalence between regression on individual or group average data I have often hear that running a regression on individual or (properly weighted) aggregated data should give the equivalent results, for example in this question or in Mostly Harmless Econometrics, ... • 253 0 votes 0 answers 22 views ### From OLS regression to Logistic Model I'm currently working on my master's thesis in finance. Without going into to much detail, my goal is to regress certain predictors on first-day returns (SPAC IPO performance). However, after ... • 101 3 votes 2 answers 128 views ### Bayesian Poisson Regression with Gamma Prior Formulas Are there closed form formulas for the posterior and evidence of a Poisson-Gamma Bayesian regression model? I was not able to find anything that is accessible online. I am not sure for which model can ... • 2,376 0 votes 0 answers 23 views ### What is the interpretation of the varImp() function Computing the variable importance of different types of models with varImp(model), the obtained results are as follows: ... 1 vote 1 answer 28 views ### Difference-in-differences if the control group is treated later Would a difference-in-differences analysis still tell me something important if the control group was treated later in time? Or, would I be better off only restricting my analysis to the time frame up ... • 23 1 vote 2 answers 33 views ### Why use transpose of nabla in gradient descent For gradient descent we have the formula: f(x_{k}+d_{k})\approx f(x_{k}) + \nabla f(x_{k})^T d_{k}  What I don't understand is, why we use the transpose of nabla and not just nabla. • 13 0 votes 2 answers 28 views ### why the p value changes when I run a linear mixed model instead of a simple regression? and how random effects affect the output? I ran two models, a linear regression model and a linear mixed model, I did this because I was suspecting that there were some levels or hierarchy in my data, specifically in my subjects and ... 0 votes 1 answer 23 views ### Difference In Differences with Daily Numbers I ran a DID regression and found my estimate on the DID coefficient to be .022. The units of time I am using are days, and at a certain day around halfway through my data, the treatment group was ... • 23 1 vote 1 answer 47 views ### Linear Regression with Lasso Regularization by using scikitlearn and scipy.optimize i am trying to apply lasso linear regression with both scikitlearn and scipy.optimize min method. However, i cannot reach same result. Code that i created with scipy.optimize can't shrink redundant ... • 13 0 votes 0 answers 17 views ### (Undergrad looking for help) In logarithmic regression (log-log), what does it mean if your explanatory variable is already a percentage? So I'm hoping to a regression of Human Development Index against some economic variables I think could affect it. Some types of aid per capita, education spending by government as a percentage of gdp, ... 0 votes 0 answers 12 views ### Is Platt scaling applicable to a small sample size? I am learning predictive modeling and recently came across the calibration technique called Platt scaling. I want to ask: Is this technique applicable to the small sample size such as my project (n=... • 311 1 vote 1 answer 16 views ### Comparing Activities with regression I am trying to find out what is the effect of activities(like jumping, weight lifting etc.) on behavior (such as attitude towards participating in a marathon). (sample size of 60 observations for each ... • 11 0 votes 0 answers 13 views ### Regression with independent variables as percentages [duplicate] I'm trying to run a regression analysis where my dependent is number of deaths and some of my independent variables are things like: poverty rate (Ex - 0.16, 0.09), incarceration rates (Ex 0.0042, 0.... 0 votes 0 answers 21 views ### What happens if the "coefficients" in the data generating process are correlated with the variance of the error term? Suppose we are interested in estimating a regression of the form$$ y = \beta x + \epsilon $$but in the data generating process, \beta is decreasing in \mathbb{E}[\epsilon^2]. For example, there ... 0 votes 0 answers 15 views ### How to reconcile model results? I have a logistic regression in which I am evaluating animal selection for various categorical landcover types (woody, herbaceous, bare), canopy cover (continuous variable), and vegetation density (... • 33 0 votes 0 answers 9 views ### Using AIC with OLS- should I use Z scores [duplicate] I apologize at the start- I am not a statistician. The first response to my post suggested I did not phrase my question properly. I have tried editing the question to focus on my primary concern. I ... 0 votes 0 answers 8 views ### Serial mediation Hayes Process 6 with SPSS; 2 mediators - issues with paths a1 and a2 I have the following issues which I would like to understand: I have recently run a Hayes Process 6 analysis. I have checked for outliers (Mahalanobis, Cook's and Leverage and excluded cases that did ... 0 votes 0 answers 18 views ### Can I compare the size of the regression coefficients of an ordinal and categorical variable? I am running an OLS regression that includes variables such as nationalism, social class, educational qualification, age, etc. as predictors of social capital (dependent variable). I want to compare ... 3 votes 1 answer 73 views ### How to deal with crossed and nested factors at the same time in a linear mixed model? I've recently started analysing the data for a project using linear mixed models but am not sure how to deal with crossed and nested factors at the same time. In my study, each participant reported ... 0 votes 0 answers 24 views ### How to interpret independent dummy variables in logistic regression? I have both quantitative and dummy independent variables in my logistic regression. Dependent variable is binary. I have 2 questions. How to interpret a quantitative variable that is negative? How to ... • 31 0 votes 0 answers 12 views ### Uniform measurement error in "errors in predictors" regression I'm working with cancer incidence data that uses a range of ages (e.g. <1, 1-4, 5-10, ...) rather than a single value. I want to fit a model where age is a predictor. As a result, I'm curious ... • 101 0 votes 1 answer 13 views ### multiple Regression Analysis for categorical and continuous varibles I'm conducting a regression analysis between a dependent variable ( continuous) and two independent variable one is categorical ( nominal , yes and no value) and the other is continuous . is the ... • 1 1 vote 3 answers 86 views ### Regression coefficients do not match conditional means In a nutshell, I want the regression coefficients of a model to match several differences in conditional means. You can download the data from this repo. I have a data set that has a dependent ... • 341 1 vote 0 answers 37 views ### Interpretation of Relative Difference in Differences Results with Relative Units I am writing a paper using a difference-in-differences analysis. My control and treatment groups are groups of 7 or 6 states that either do not or do undergo a certain policy. I ran my difference-in-... • 23 0 votes 0 answers 8 views ### Empirical risk minimization for relu/max loss function Classical risk minimization (RM) minimizes the expected loss over the training distribution p_{\mathrm{train}}(x),$$\theta^*_{RM} = \arg \min_\theta E_{p_{\text{train}}}[\ell(x, \theta)]. As the ...
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Consider a linear regression $y = aX + b$, where mean(a) = 5, SE(a) = 0.5; and mean(b) = 3, SE(b) = 0.1. When a and b are constants, $Var(Y) = a^2 Var(X)$. Do the SE's make a and b non-constants? If ...