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Questions tagged [regression]

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

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conditonal / segmented regression

I have a general question regarding the methodology of "conditional" or "segmented" regression. I have a data set of values (x,y) and I am interested in defining a model for y as a function of x at ...
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2answers
26 views

regression tree vs linear regression

I'm using one explanatory variable in a regression tree and in a linear regression. The tree finds a split (with variance reduction splitting rule), though R2 is pretty small (0.2). On the validation ...
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0answers
18 views

Partial Collinearity in Regression

I had a doubt about the effect of multi-colinearity in regression analysis. I understand if two variables are co-related we cannot disentangle the effects of one from the other on the target variable ...
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10 views

Event Study: Event time coefficients vs post change coefficient

I have an event study regression with an unbalanced panel. I include unit and time fixed effects as well as a linear time trend control: $Y_{st} = \sum_{\tau \neq -1} \delta_{\tau} \mathbf{1}(YS_{st} ...
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1answer
28 views

Question about interpretation of a fixed effects model

I am trying to see the impact of a group of similarly-minded policies and programs which were introduced at various dates in various Canadian provinces on a measure of student satisfaction. I plan to ...
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0answers
10 views

Interpreting R nnet output Multinomial Regression

I was wondering if anyone would be able to help me interpret my results. I am struggling to find anywhere online which it simple to follow. I have conducted a multinomial regression. I have a ...
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1answer
20 views

Interpret effect of covariates in linear model with log-transformed response variable

I am having difficulty interpreting the effects of the covariates of a linear model with log-transformed response for two specific time points. This is the model: $log(Y_t) = \beta_0 + \beta_1 * X_{...
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0answers
9 views

Help with saving stats in rms bootcov [migrated]

I'm trying to save the distribution of R2 values as I bootstrap a model, using the ols and bootcov functions in the rms package. ...
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2answers
33 views

Can I use regression to analyze relationship between rating and choose-all-that-apply data?

If I sent all of my customers a product to try, let's say it is a laundry detergent product. I then ask them to rank their liking of this product, from 1 to 9. then I ask them 'which words do they ...
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1answer
42 views

Is the difference between the residual and error term in a regression just the ability to observe it?

According to what I read online, the error term and the residual are often interchangeable. Please let me know if my understanding below is correct: However, the difference is that the error term is ...
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0answers
18 views

law of iterated expectations doubt

Is it correct to do so: $E(X^{-1} Y) = E_x(E(X^{-1} Y \vert X) = E_x(X^{-1} E(Y \vert X)) $ Are we allowed to use LIE in case of non linear functions like $X^{-1} $
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0answers
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The least squares estimator for beta in matrix notation in connection to normal equations and orthogonal projection in linear algebra [duplicate]

Somebody posted this link here about DERIVATION OF THE LEAST SQUARES ESTIMATOR FOR BETA IN MATRIX NOTATION-(https://economictheoryblog.com/2015/02/19/ols_estimator/). My question is 'How does THE ...
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1answer
26 views

How do you use panel data to isolate the relationship of interest for a particular individual within your panel?

I have a panel data set where Canadian provinces are the individuals. (I have annual data from 1997-2017). I am using a random effects model to see the impact of an explanatory variable $X_{it}$ on ...
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1answer
42 views

regression basic doubt

If have a simple bivariate regression model: $ Y_i= x_i \beta + \epsilon_i $ where $i$ are the number of observations. How do I test for the hypothesis that the OLS coefficient $\beta$ does not ...
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0answers
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When is the sum of model predictions the prediction of the sum?

The response variable in a regression problem, $Y$, is modeled using a data matrix $X$. In notation, this means: $Y$ ~ $X$ However, $Y$ can be separated out into different components that can be ...
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What is most important in building a regression model? [duplicate]

When I build a regression model, which is considered most important: removing insignificant variables, checking jfor multicollinearity and removing those variables that contribute to it, multiple R-...
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1answer
35 views

Variables measured on two different scales

I am dealing with three continuous predictor variables (corolla tube width, corolla tubedepth, corolla inclination) and a discontinuous response variable (counts of bee visits). I am confused on how ...
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1answer
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Intuitively, how does the wild bootstrap work?

I am trying to understand the intuition behind the wild-bootstrap. What is it actually doing? I need to be able to understand what it is trying to do compared to a conventional regression. My data ...
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0answers
32 views

Cross validation for time series prediction: How to choose the best model from different neural networks?

I want to choose the best model from a list of neural network models. My problem is a multivariate time series forecast (regression) problem, in which I forecast a parameter using other parameters, up ...
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3answers
45 views

How can I find maximum source of variation in a linear relationship?

Probably very basic for most of you, but I am just starting out in statistics so please pardon my ignorance. I have a significant positive relationship between body mass (Y) and elevation (X). I ...
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0answers
8 views

Statistical significant difference between two regressed models with use of confidence intervals

I wonder how to decide if two regression models are significantly different at a location X. Here is an artificial example, $\hat{Y}=a+b\cdot X+c\cdot X^2$. The graph shows the (artificial) measured ...
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1answer
32 views

Testing whether two categorical variables have identical coefficients

I am currently doing an exercise question asking me to construct a model to test whether the coefficients of two categorical variables ($X_2$ and $X_3$) are same in R. Specifically, these two ...
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0answers
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Is it useful to use sparse regression (e.g. Lasso) when the number of observations is significantly larger than the number of covariates?

I'm learning about penalized/sparse regression and I noticed that the examples used for penalized/sparse regression, e.g. Lasso, are usually cases where the number of observations is significantly ...
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1answer
46 views

Repeated measures correlation as mixed model

I'm writing this question to better understand how to set up a mixed model to estimate a linear relationship between two variables from repeated observations. Suppose the variables $X$ and $Y$ are ...
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0answers
14 views

Representing a dataset with non-normal errors

I have looked at several sources and cannot find any guidance, but perhaps I'm using the wrong terminology. I want to represent a dataset by regression line and variation similar to the way you would ...
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0answers
13 views

Correlation and Regression analysis

I have two theoretical questions: 1) In a correlation analysis for example sales x price, if I have monthly sales data with a very large variability and with a non-normal distribution, do I need to ...
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1answer
26 views

How to use features in regression model with 2 of them in linear relation with the value to be predicted?

I am relative newbie to data science so please excuse me if its a trivial question. I have 6 features and want to predict the 'y'. These features are related to y in the training data-set as follows; (...
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0answers
21 views

Endogeneity and Consistency

So I learned about the endogeneity problem of linear regression in class today, where E[XU] and Cov[X,U] isn't equal to zero but some random constant c times a standard basis k-element vector with 1 ...
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0answers
26 views

transform X to predict Y

I have (x,y) data where x takes on the integers from 2 to 100 and y is a continuous variable. I want to smooth the data with a polynomial regression of y on x, but I know that varying x from 2 to 3 ...
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0answers
14 views

Regression model for difference-in-differences analysis with two post-periods

I'm attempting a difference-in-differences analysis with one pre-treatment time point (0), and two post-treatment time points (1, 2). I'd like to know, firstly, whether there's a significant ...
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0answers
34 views

Goodness of Fit in linear regression - to me this is not a [duplicate]

The link that is supposed to answer my question neither mentions $R^{2}$ nor GoF. At least I do not see it. What is the name and the formula to calculate the GoF in that link? Both should exist for a ...
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0answers
37 views

Estimating errors in a least square linear regression

Suppose I have a linear model of the form: $$\mathbb A \mathbf x = \mathbf y$$ where $\mathbf x\in\mathbb R^p$ is a vector of parameters, $\mathbb A\in\mathbb R^{n\times p}$ a known matrix, and $\...
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ZINB error code in winbugs: order of negative binomial y[1] must be an integer [migrated]

I have a problem while running ZINB regression using Winbugs, it keeps showing "order of negative binomial y[1] must be an integer" when I click "gen inits" in the Specification Tool tab. This is my ...
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3answers
38 views

How can we plot the predictions of logistic regression model in order to see whether it is good?

I am working on a basic problem that requires developing a logistic regression model (the output is True/False, whether a person gets cancer). I have used glm() in R and got the model with some ...
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1answer
51 views

Can Logistic regression be used as a Linear Regression model [closed]

In a question I'm given Construct a linear model and see how well the fat content can be estimated. That is, estimate the generalization error with a linear model. Optimize the number of ...
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0answers
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How to determine which variables are statistically insignificant in multiple regression?

Currently, I am using R to analyze data. The data has 5 columns to it (glucose, glucose tolerance, insulin, insulin resistance, presence of diabetes(yes or no), presence of diabetes in numerical value(...
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0answers
28 views

Literature on conceptual understanding of beta regression

I am researching beta regression models to decide if they are appropriate for my data. My very first search yielded this basic introduction, that also describes the zero-one inflated beta regression. ...
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1answer
43 views

How to calculate the coefficient of a dummy variable reference category?

I am currently building a regression model with numerous continuous, categorical (employing dummies) and interaction variables. I understand we must use k-1 dummies with one variable becoming the ...
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0answers
22 views

The strength of negative regression coefficients

I realize that this is likely a dumb question, but does a logistic regression coefficient of -.222 demonstrate a stronger effect than a logistic regression coefficient of -.087? The negatives confuse ...
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1answer
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Interpretation of regression tree with Poisson data

Above is a decision tree made by following code ...
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1answer
35 views

Training error less than validation error, but higher than test error?

I have a time series regression prediction problem. So I divided the dataset into 3 parts: training (first 70% of the time series data) validation (from 70% to 85% of the time series data) test set (...
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0answers
31 views

Which regression model for percentage data with many zeros and ones?

I am analysing the share of a tree species at different forest locations. The data I am using is in percentage of the total species composition and I am modelling it based on the climatic probability ...
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0answers
29 views

Does centering really help interpret the intercept? [duplicate]

Various people have advocated centering independent variables in regression, on the grounds that the intercept then refers to a sensible point (the mean of each IV) rather than the often impossible ...
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2answers
36 views

What is the difference between Local Linear Regression (LLR) and Locally Estimated Scatterplot Smoothing (LOESS)?

I've looked into nonparametric regression packages in R and Python and came across two estimation methods that are relevant for my problem (i.e. replicating the semiparametric estimation in Carneiro, ...
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2answers
1k views

Is random forest for regression a 'true' regression?

Random forests are used for regression. However, from what I understand, they assign an average target value at each leaf. Since there are only limited leaves in each tree, there are only specific ...
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0answers
42 views

How can I fit a multiple linear regression model in R if the value for beta coefficient of each predictor is given? [closed]

I've got an exercise question asking me to fit a multiple linear regression model in R when the values of coefficients are given. I don't know how to do it. specifically, I have 5 predictors in my ...
2
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1answer
24 views

adjusted R squared for multiple exact same input variables

I was trying to understand how adjusted $R^2$ in a simple linear regression behaves when there exists multicolinearity. And realized I could not replicate the adjusted $R^2$ provided by excel data ...
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2answers
92 views

Suggestions on Modeling Approach to Model Percent Complete of a Task

I am trying to predict what percentage (or proportion) of a task is completed by various workers, given the time left until the deadline to complete the task and I'm looking for help on how to ...
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0answers
21 views

Which algorithm should I use to predict the winner/loser of a competition, among 5 competitors?

I hope I posted in the correct session. I need to solve this "simple" problem. PROBLEM EXPLANATION I need to predict who is more likely to win a car race, among 5 drivers. I have a database that ...
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1answer
23 views

Residual vs fitted values (large outlier in predicted value?)

I have attached a plot of residuals vs predicted values for a model i ran. I see 1 large predicted value (extremely large compared to the others) is this a problem for my model? and if so, what can ...