Questions tagged [regression]

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

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Mathematical formula for interaction term in multiple regression with two predictors

I am trying to understand the math behind the coefficients in a multiple regression with two predictors and their interaction. I know that this can be done in matrix notation OR directly in any ...
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Non-Parametric Regression with an Omitted Variable

Suppose we use the Kernel Regression Estimator $$\hat{m}(c)=\frac{\sum_{i=1}^n K\left(\frac{x_i-c}{h}\right)y_i}{\sum_{i=1}^n K\left(\frac{x_i-c}{h}\right)}$$ where $h\to 0$ and $nh\to \infty$ as $n\...
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How to make the profile likelihood model for estimation?

I tried to make the age estimation model using the chemical compound results from The soil. Initially, I used the multivariable regression model. However, the reviewer highly recommend using the ...
user21268575's user avatar
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regression paradox

I have to do a binary logistic regression with two dichotomous independent variables. I found myself faced with a paradox that I don't know how to handle. In the complete database I have 21 (5.6%) ...
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When assessing significance of identification variables (e.g., race) after applying a regression model, is it correct to use a Bonferroni adjustment?

I am building a regression model to assess whether being a member of any particular race (compared to the control group, which is White) is associated with a statistically significant loan application ...
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Which statistical tests to use for aggregated data?

I am writing my finance bachelor’s thesis on the impact of Covid-19 on household’s portfolio choices across different wealth groups in the BeNeLux area (Belgium, Netherlands, Luxembourg). The data ...
Lukas Peric's user avatar
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Intersection of restricted cubic spline with log relative hazard = 0

I would like to determine the intersection of a restricted cubic spline with log relative hazard = 0 (i.e. the change from a lower hazard to a higher hazard). Thank you! ...
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Can exponentiated coefficients in multinominal logistic regression (with softmax normalization) be interpreted as odds ratios?

Exponentiated logistic regression coefficients are interpreted as odds ratios. Does this still hold in multinominal logistic regression, where softmax is typically used to normalize probabilities to ...
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How to Run Regression with Replication in R

Looking to see if anyone knows how to run a regression analysis with replication in R. I have a data set with multiple values of Y for each value of X. I could take the mean of the Y values, but that ...
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Estimating optimal number of trees in gradient boosted trees

I was trying to come up with the formula to estimate the optimal number of trees in gradient boosted trees (I understand that using early stopping or cross validation is a better approach in practice, ...
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Deriving the F-Statistic for a new experiment

I am working on a homework problem, where I have been given the following information: Using this information, I was able to replicate the ANOVA table. However, I am asked to compute a t-test ...
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Does It Make Sense to Use Random Forest When Predictor Values Are Averaged by Groups?

In a nutshell: does it make sense to use Random Forest for analyzing the importance of predictors when predictor variables are averaged by groups of samples? I'm working on an ecological data analysis ...
Jose Antonio Morillo Perez's user avatar
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Discovering a natural grouping structure in data

I'm looking to apply some data using the sparse-group lasso. This method requires that the variables sit within groups, so I need to pass group labels to the model. Is there an efficient method for ...
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What is the name/terminology for this application of OLS regression

I don't come from a statistics background and was instructed to follow these steps to fill in missing data. I'm wondering if there is a name for this specific method so that I can learn more of it and ...
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Feature dependence in Random Forest application

I'm applying a Random Forest Regression on target variable y, number of items bought At the time of running the regression, I will have access to the 'running total'...
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Combining regression models based on missing data patterns

I have a dataset that contains a few patterns of missingness. For this dataset, I have a training set that is complete and contains all input features. My test set has complete observations for the ...
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Lag-Augmented Local Projection and Standard Errors

Let's assume that I have some data series $y$ and I am interested to estimate a regression of the dependent variable (DV) on the lag of the DV. Formally, we assume a simple AR(1) model such that $y_t=\...
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How to compare mediation models with one or two mediators?

I'm looking to compare the indirect effect sizes of two models: IV1 -> IV2 -> DV and IV1 -> IV2 -> IV3 -> DV Is there a way to do this in R? I know how to run the first model using the ...
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How to implement Newey-West standard errors in R?

Im trying to implement newey-west standard errors to correct for issues i had with autocorrelation doing a regression with OLS. But these robust errors only make my results less significant. I have ...
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Model Fit Measures in a Binomial Logistic Regression

I am very new to regression statistics and have produced four models in the statistical package Jamovi using binomial logistic regression. Looking at model fit measures I am confused as the results ...
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Proportion mediated possible for Binary outcome, Continuous mediator?

I am running a mediation analysis on a categorical X (race/ethnicity), binary Y (disease status), and ordinal M (can be any integer 0 - 10). N-controls = 1321. Ncases = 384. I conducted this analysis ...
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Is it correct to evaluate response histogram to decide between a normal regression and other GLMS?

everybody I'm learning about linear regression and GLM's. One of the things I see is the affirmation that: I can make and histogram of the response $y$ and if it don't follows a normal (for example ...
Roger Danilo Figlie's user avatar
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Diff-in-diff with balanced panel: adding fixed effects does not change coefficients?

I'm trying to run a differences-in-differences model in Stata. My dependent variable is order volumes, each observation is 1 store, and my panel is strongly balanced (20 quarters for each store, 6K ...
Mike's user avatar
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Fixed effects regression: reghdfe vs reg with dummies (stata)

I am trying to understand what is the difference between running a regression with a bunch of fixed effects by directly creating the dummies versus using reghdfe. Below a minimal working example: <...
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What is the difference between standard deviation and the second derivative of a function in terms of measuring the function's convexity? [closed]

Not sure if this is appropriate for another Stack Exchange, feel free to redirect if it is. As the title suggests - What is the difference between standard deviation across $f(x)$ with $x=1,2,3...$ ...
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How can I test if lower values on my regression line come from a level of a grouping variable?

If I have continuous x and y variables I can fit a simple regression. But I want to know how can I test if the lower and upper values of my variables are associated with different groups as in the ...
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Equivalent GLM's for common stabilising transformations

I'm familiar with applying a log-transform to a skewed outcome variable to improve model fit, but I've not thought further to link stabilising transforms to GLM's in general. Reading around it seems ...
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Initialising Multivariate linear regression with the maximum likelihood method

I am attempting to use maximum likelihood estimation to fit a multivariate linear regression problem. I have 5 predictor variables and a similar number of response variables. I am using a correlation-...
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R issue: lm() is printing NAs for rows once ncol > nrow [duplicate]

I'm running an lm() on lagged variables as part of a network analysis, and have the following dimensions: dim(final) [1] 197 277 dim(final_lag) [1] 197 831 The ...
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Regression for Likert scale SPSS

I have taken a survey. Dependent variable is on Likert scale (1-5). Independent variables are also on Likert scale 1-5. What kind of regression should i better use? I thought about multinomial (or ...
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How do I quantify the effect of a factor with many levels?

I want to look at the effect of brood ID on fledging success (a binary variable) in a sample of wild birds. Brood ID has ~150 levels. I have performed a likelihood ratio test comparing two logistic ...
Emadeel's user avatar
2 votes
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Appropriate stats model for time data with an upper limit?

I'm struggling to settle on a statistical approach for a portion of my dataset. Any thoughts/insight would be appreciated. Subjects (divided into two categorical groups) were given up to an hour to ...
Stats Newbie's user avatar
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log odds visualization vs. probability visualization

This is more a conceptual question. I have the following logistic regression model in R: ...
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Evaluating GLM with Gamma distribution vs. transformed response for predicting right-skewed price data

I am trying to predict house prices using a dataset with the following variables: ...
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How to derive conditional posterior predictive distribution from definition of posterior predictive distribution in bayesian regression?

In my situation, I have a set of data points: $$ z_{0:n} = \\{ (x_0, y_0),\dots ,(x_{n-1}, y_{n-1}) \\} $$ I am trying to figure out how to derive the fully expanded form for the conditional posterior ...
QMath's user avatar
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Which statistical test to use with binary dependent variable and three independent variables?

I have a dataset that consists of a binary dependent variable (success/failure) and three categorical independent variables (geographical aspect, temporal aspect, and participant type, all of which ...
Airy's user avatar
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Causal Mediation Analysis with treatment smoothed in the outcome stage and linear in the mediator stage

I am considering a mediation analysis that looks like the following in r: ...
flâneur's user avatar
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Regressors Became Statistically Insignificant Upon Correcting for Autocorrelation

I am using Stata and used the regress command and received $p$ values that indicate the regressor is statistically significant. However, after plotting the residuals, I noticed there was clearly an ...
William H's user avatar
3 votes
2 answers
92 views

Replicate t or F test from regression using regression likelihoods

I've heard that the t-test and F-test we use to get the significance of our regression results are derived from the likelihood ratio test, but I'm having trouble replicating the p-value of the t/F ...
A Friendly Fish's user avatar
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Unable to get heteroskedasticity-robust standard errors for PLM "between" model

I am presently running a regression on a balanced panel dataset, where I observe +1000 individuals over a T=10 time period. Given that individual specific independent variables remain constant over ...
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"How can I address the lack of correlation and a low R-squared value in my univariate linear regression when the data is scattered?"

** "I'm trying to find a correlation between the confirmed cases and deaths rates against HUMIDEX values. As you can see, the data is very scattered, so I understand that polynomial and ...
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Handling missing values in GAMs

I am currently fitting a GAM-model, which assumes that the price of a house P can be modelled as a sum of smooth effects from different distances $d_{1}, d_{2}, ...$, e.g. distance to coast, lake, ...
August Edwards's user avatar
3 votes
2 answers
169 views

Range of OLS regression coefficient when combining disjoint datasets

How would you approach the following problem? We have two disjoint datasets, $\mathbf{X}$ and $\mathbf{Y}$. We can separate them into $\mathbf{X}_1 (A\times 1)$, $\mathbf{X}_2 (B\times 1)$ and $\...
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A good variable to make a regression model for gas usage over the years for a city

so I'm new to statistics, I'm trying to make a regression model in Excel, explaining why, or due to what variable, does the gas usage change over the years. I tried using a basic Y variable - Time - ...
Nero's user avatar
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1 vote
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Multinomial logistic regression 0 classification rate

I am running a multinomial logistic regression with SPSS and I have encountered a problem (?) with my data. I have a dependent variable: foreign language enjoyment (FLE) (DV) with five categories ...
Vivien Gao's user avatar
1 vote
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How can I combine/pool the results of regression ANN?

In my analysis, the data contains 5 imputed dependent variables. So, after analyzing all of the dependent variables separately with a regression neural network, I need to combine/pool the results. ...
minre's user avatar
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1 answer
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SEM with 50% missing data (due to distribution of items over various survey ballots/waves)

I want to test a multilevel mediation (particularly, test a number of hypotheses about possible mediators of the effect of social class on Right-Wing Authoritarianism) using largely categorical ...
ThomasV's user avatar
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1 vote
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Modeling no-show rates of attendees in R

I'm trying to determine to what extent the no-show rate of registered candidates to a (past) event is dependent on the weekday that the event was hosted on. Given a number of past events that have ...
Marco W.'s user avatar
1 vote
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How adjust regression coefficient by sample size?

Suppose I have two time series, $\{X\}_{t}$ and $\{Y\}_{t}$ with significantly different lengths, $n$ and $m$ observations, respectively ($n>m$). I want to estimate the following AR(1) models: $$X_{...
Sane's user avatar
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Knockoff R package removing ALL variables based on LASSO, Why?

I am simulating a data set from a linear regression model and selecting the variables using LASSO (glmnet). The selection works relatively well with ...
Jack's user avatar
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