Questions tagged [regression]
Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
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Regression models after PCA
My understanding of principal components regression (PCR) is that it is a linear regression performed on all or a subset of predictors obtained via PCA. All the resources I've read only apply linear ...
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Study of an experimental regression with a percentage as the dependent variable
I am trying to estimate the effect of an experimental intervention (random assignation to treatment and control groups) with the percentage of people in each group assisting to government services as ...
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What model should I use for this weird dataset? (Survey Response attributes)
Above is a snippet of a dataset I am working with. It is a pull from a research tool presenting a set of many different and distinct attributes that have been sorted into numerous "categories&...
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Test and Train AUC are almost exactly the same
I am trying to build a logistic regression model. My test and training sets are generating almost the same AUC. Ideally- this means that the model is performing very well. But since, I got this result ...
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Computing gradients of Gaussian Process Regression [closed]
I have a dataset with 2 features in it, I would like to obtain gradient for this case. Can anyone help me with this. I am looking for 2D solutions, partial derivatives with respect to x1 and x2.
def ...
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How to analyze the interaction between variables when the number of explanatory variable is large
I am interested in the analysis of interaction between variables in a regression model.
First, the context : I work in marketing and the explanatory variables corresponds to marketing channels, ...
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Visualizing Multicollinearity: How does overlapping region of IVs contribute to R²?
I have trouble understanding how R² in a regression analysis makes sense visually in Ballantine diagrams.
For instance:
Obviously the red region is ignored when estimating the coefficients for x on y ...
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Relationship between conditional expectation and regression
I would be grateful if you could help me clear up some confusion regarding conditional expectation and regression.
I have seen two formulations of the linear regression framework:
$$Y=a+bX+\varepsilon\...
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Intercept in Quantile Regression
We all know that for the OLS model, if you center both $X$ and $Y$, the estimated intercept would be 0. I was curious if we can do a similar thing for Quantile Regression. Would it be possible if we ...
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Can we see relationship between two index variable
In multiple linear regression model can I use dependent variable as index (composite food security index) and also one independent variable as index. For example livelihood vulnerability index for ...
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FRW bootstrap in R
I am working on a logistic regression problem with 2 classes (let's say 0 and 1) where the positive class (1) is rare. In this case, I have found that Fractional-Random-Weight
Bootstrap (FRW) is a ...
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Difference between four random effects structure
What is the difference between the following four random effect structures in R?
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Testing sum of dummy variables
Say that you had data for the point spread of a basketball game: Team A points - Team B points (where team A is the home team and team B the away, if there is no home and away team, then team A is ...
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Should you deflate prices by index when doing multiple regression? [migrated]
I have data ranging from 2008 - 2016. I have been studying effects on the %satisfaction of creditors in debt relief (Czech Republic). I have used modified "One vs. All" method, where I forgo ...
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How to specify random effects for panel/longitudinal data with level 2 predictor?
In the study of tweets pre- and post- metoo (set as Nov 2017), we are looking at whether there is gender differences in the use of masculine language in tweets for male and female social media users.
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while calculating the slope of a regression line, why do we multiply the slope by the correlation coefficient when it can only decrease the steepness?
Given that that correlation coefficient can only be between -1 and 1, it can never increase the steepness of the slope when calculating the steepness of a slope in a regression line.
Say correlation ...
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Issues with generating Odds ratio in R [closed]
why am I getting the error message that my R could not find the function odd ratio? although I have used them recently.
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SAS procedure for calculating LOC Line-of-Organic-Correlation?
I am using SAS PROC Reg to develop an OLS regression equation for a random sample of 190 observations. These observations contain the Old_Area of_oF_Polygons (var X) and the true area of GIS polygons ...
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GARCH (sGARCH) with ARFIMA (ARIMA) model in Rugarch equation formula output
Could you please help to write down the exact equation?
It is clear for Garch part but not clear how to add ARFIMA (1,0,1) or here just ARMA(1,1) in model equation specification.
Should we also type ...
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Calculate log-likelihood of logistic regression
I am trying, without success, to calculate the log-likelihood of the most basic logistic regression model - a constant probability model (i.e. only $\beta_0 \ne 0$).
For the simplest model with 1 ...
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small dataset for a regression task
I am trying to train a NN model in MATLAB to predict the amount of overflow for flooded junctions in an urban runoff system and I have 45 samples and 15 features. The issue is, I don't think 45 ...
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How important are the Gauss-Markov assumptions for linear regression?
When studying through the book Introductory Econometrics, we see that Wooldridge list 5 assumptions in order to get the BLUE estimators (Best Linear Unbiased Estimator) in Linear Regression: linear ...
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regression modeling - logistic
My task is to run a logistic regression that models the probability that revenue is non-zero (in the
logistic regression parlance, a positive revenue is a success). Revenue variable is numeric and ...
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Changing scale and rounding off Target
I am training a regression machine learning model to predict an airplane's maximum take-off weight based on some pre-project features. The airplane weights in the dataset I'm working with are ...
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GLMM with non-integer "count" data
I'm looking at the difference between bird communities across 5 different vegetation condition levels. Bird species richness data has been recorded across 40 sites, with uneven sample sizes for each ...
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Calculating Change in OR per increase from the 25th to 75th percentile (IQR)
I have a dichotomous outcome variable (ever disease) and a continuous exposure variable (chemical). I have already run the logistic regression for the ln exposure and gotten the odds ratio. However, ...
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Multiple cases, each having multiple time seies
I have multiple cases, each having multiple independent variables measured over time. One of the variables represents known failure/success in the past, and I am trying to model a binary logistic ...
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Interpretation of coefficient on an interaction term of log(continuos x)*log(continuous y)
I would like to ask a question regarding the interpretation of log-log interaction term in the Two-way fixed effect model. I have the following regression model:
y_it = 𝛽_0 + 𝛽2[ln(price_it)*ln(...
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Synthetic control method based on several treated units
I am trying to causally evaluate an impact of a specific labor policy that was implemented in three U.S. states. I wonder if constructing a synthetic/artificial control method (SCM) for those states ...
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Statistical test for interpreting negative coefficients in multivariate cross sectional analysis [closed]
I wrote a seminar paper on the conditional ß-convergence (income convergence) of the Solow Model and therefore ran several cross sectional regressions in R. Thus, I regressed the variables "GDP ...
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What does extrapolation mean in the context of regression weights and what are its downsides?
In numerous articles I have read (Abadie 2021, Samii 2016, basically any Abadie piece that talks about the synthetic control method), the authors cite regression's reliance on extrapolation for ...
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Transfer a regression model from sample to raw data
Suppose that I have a single regression model predicting daily total store sales. Initially the model was trained on only 1% sample of the data and I applied min max normalization to the store sales. ...
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How can I format a double entry table into a long table in R to run a linear model? [closed]
I need to run a linear model of some data. I was given a 'double entry' table. Until today I was not familiar with them. This is how it looks:
Every row has a value of the dependent variable, except ...
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How to simulate variability (errors) in fitting a gamma model to survival data by using a generalized minimum extreme value distribution in R?
As shown below and per the R code at the bottom, I plot a base survival curve for the lung dataset from the survival package ...
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What is the difference between a piecewise SEM versus a GALAMM for GAMM-based SEMs?
Question
I was just reading the article here regarding the use of generalized additive latent and mixed models (GALAMMs), which are purportedly a form of multi-level structural equation model (SEM) ...
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Budget allocation using multiplicative regression model
I need your help to define the optimal budget allocation using a marketing mix model. I have built a multiplicative model to account for diminishing return and interaction between my IVs, and I am ...
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rank in a partitioned regression
Let us consider a regression model
$ y = X_1 \beta_1 + X_2 \beta_2 + u $
where $y$ is $n \times 1$, $X_1$ is $n \times p_1$, $X_2$ is $n \times p_2$. Assume that $rank(X_1)=p_1$ and $rank(X_2)=r_2 \le ...
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MLE estimation of scaled regression
Let's say I have a univariate (no intercept, for simplicity) regression with normally distributed errors,
$$y_i = \beta x_i + e_i, \text{ where }e_i \sim N(0,\sigma^2),$$
And I would like to find MLE ...
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Interpreting simple slopes in OLS regression with multiple interactions
I dug through previous simple slope/effect questions and couldn't find what I was looking for, but happy to be pointed to it if it exists.
On p. 17 of Jaccard and Turrisi (2003), they offer the ...
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Estimating joint probabilities across two datasets
I would like to estimate the joint probability of two variables from two different surveys conditional on other variables that the two surveys have in common.
As an example I'm using data from this ...
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Regression with a sum of variables and a proxy
I want to estimate the coefficient $a$ in the regression
$$ P = c + aX + bY + u $$
However, I only have the variables $T = X+Y$ and $\tilde{Y} = \mu_1 + \mu_2 Y + e$. If I had the variable $Y$, then I ...
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Does binomial regression weight some observations more heavily than other?
I am performing a quasibinomial regression, where each subject has an unfixed number of trials. So one subject may have had 5 trials while another had 90. In R the regression equation follows:
glm(...
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Analysis of causal relationship of within-subject choice patterns among different groups using R - emmeans / hlm / Mixed Effects Logistic Regression
I am conducting a research and investigate the relationship between persona type (independent variable; a vs. b vs. c vs. d) and luxury perfume choice (dependent variable; niche vs prestige)(H1), ...
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How to test for size (Typ one error probability) on Breusch-Pagan Test in R?
The data i created contains heteroscedasticity. I already calculated the power so my idea was to basically do the same but switch the hypothesis so that H0: Heteroscedasticity and H1: Homoscedasticity ...
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Parameter distribution of $\theta$ from a rectangular matrix multiplication $C\theta$
I am struggeling to see where this problem fits - i.e. what topics this problem relates to, so I am not able to find the right literature. I want to use some particular information as a prior to a ...
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Seeking for help! About conducting hierarchical linear regression with categorical variable as moderator by using SPSS [closed]
In my thesis, I have made the following hypotheses...
IV--> Perceived Risk of COVID-19 (Continuous variable)
DV --> Anxiety (Continuous variable)
Possible moderators--> age, education level, ...
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Estimating and fitting a GARCH model
By far I've become really familiar with the concept of GARCH but I'm still confused on how to go on with the implementation especially that I've seen multiple sources using different approaches:
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Non-linear regression. Need some help implementing a model from a paper
I found this paper very useful for my research, however, I'm not familiar with non-linear regressions and I'm finding it tricky replicating it.
Using the first f=model for example:
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Why does this multiple linear regression fail to recover the true coefficients?
I am trying to use linear least squares regression to extract the coefficients of a model. Specifically, I am looking at a model with two independent predictor variables $x_1$ and $x_2$, and an output ...
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Known coefficient in multiple linear model
Lets say my model is :
$y=\beta_0+\beta_1x_1+\beta_2x-2+\beta_3x_3$
Now lets say I know for sure that $\beta_2 = 4$.
My teacher said I should create $y’ = y-4 X_2$ and ordinary least squares (ols) ...
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