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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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How to interpret a negative coefficient in logistic regression?

This is the summary of a fitted model on Titanic dataset in r ...
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1answer
21 views

Is ordinal regression a classification or a ranking problem?

I’m confused, in wikipedia, ordinal regression is also referred as ordinal classification. Which makes sense since ordinal variables are in the end just categorical. On the other hand, ordinal ...
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1answer
27 views

Model selection based on Adjusted R Squared (Backward) in R [closed]

model.all = lm(price ~ . - id , data = sample_n(hs, 500)) step(object = model.all, direction = "backward") The step function ...
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Combining regression models from separate data sets

What is the best way to combine regression betas from separate data sets? For example, a data set is split in two based on some fundamental characteristic, and the same two factor regression is run ...
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4 views

Is a linear regression analysis the right thing for cohort event correlation?

I have a table like this, except with hundreds of events and 10 user buckets. If I wanted to answer the question: what event is Cohort A statistically more likely to do as a proportion of the ...
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11 views

Exposure in Poisson regression

Could somebody explain the concept of exposure in the context of Poisson regression and how it relates to the expected value of a Poisson distributed response?
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559 views

Why is linear regression results so much different from Poisson regression?

I ran both a linear regression and Poisson regression on count data (data ranges from 0-54) with two continuous predictors and the p values were very different between them. ...
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17 views

Data analysis: Investigating whether a policy is implemented or not

Consider a dataset consisting of student wait times for a large number of experts for two periods. Between the two periods,the school may have altered experts’ capacities based on observations of ...
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1answer
25 views

Controlling for variables in social sciences

I know this is a completely hypothetical scenario but I just want to understand how the effect of a variable could be held constant and how the coefficients of two independent variables are estimated ...
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18 views

Stationarity in logistic regression

For a time series dataset, is it required for the independent variables to be stationary for logistic regression? If yes, how can we check for stationarity?
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Signal to noise ratio for structural equation models

Consider the linear structural equation model with known $\beta$ as $$ SEM \quad X_k = \sum_{j=1}^{p}\beta_{jk}X_j + \epsilon_k$$ where $X_k$ is a random variable. I construct a data matrix $D_{m \...
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1answer
37 views

What is the probability the two estimates of residual variance for the two models are equal?

I fitted two models using linear regression in r: Analysis of Variance Table ...
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9 views

Interpreting Random Effects for 3-level Multilevel Model

I made a land value analysis using a random-intercept multilevel model with 3 levels (lands nested in districts further nested in cities). The intercept is allowed to vary between each district and ...
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8 views

Generalized Residuals for Control Function Approach in R [closed]

I am trying to estimate a tobit model with the control function approach. For the first step I am running a logistic regression on an endogenous binary choice dependent variable. I have the following ...
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1answer
36 views

Build model for daily probability of meeting a certain end of period goal

I was hoping for some consultation with how to go about the following: To give context, I work for an agency that manages advertisements on social media for general motors - specifically their car ...
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11 views

Using GridSearchCV with TimeSeriesSplit [closed]

I have some code that would use TimeSeriesSplit to split my data. For each split, I would use ParametersGrid and loop through ...
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0answers
43 views

When to choose regression splines over smoothing splines? [duplicate]

I am currently studying how to model covariates beyond linearity in order to use them with GAMs for regression / classification purposes. Talking about splines, two types were presented: regression ...
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13 views

Interpreting a 2 x 3 design with two empty cells

My psychology grad student and I have a study conducted in three different countries using two different method variants. Neither country nor method variant is a predictor of focal interest, but might ...
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5 views

multiple imputation for k-means clustering + outcome variables

I’m exploring whether distinct clusters can be derived from real-time, smartphone logs of daily social behaviors, and how these clusters predict self-reported depression and loneliness. My plan is to ...
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My standard errors are smaller when I use Newey-West? HELP!

I am looking at some time series regressions, When I use OLS, my standard errors on one of the coefficients is 0.002777409. When I use the Newey-West correction the standard errors are smaller: <...
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42 views

Logistic regression or linear probability models

Here, I will ask a question which always seemed trivial to me as an application focused person studying political science: Do I use a logit model or an LPM when modeling categorical data? Up until ...
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1answer
54 views

Multicollinearity in simple linear regression

If there's perfect or near multicollinearity problem in a simple linear regression $y_i = a + b x_i + u_i$, what characteristics does $x_i$ have? I think if there's perfect multicollinearity, it ...
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1answer
18 views

Transfer learning for regression problems?

How does transfer learning work for regression tasks? Can someone point to an application where transfer learning has been successfully applied for regression tasks.
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1answer
15 views

Relative importance of metrics in linear regression

I am trying to compute the relative importance of regressors using the relaimpo package. In the linear model, some regressors are insignificant (p-value greater than 0.05). Should I include these ...
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1answer
56 views

I Need Help With My Data [closed]

What type of data would whole numbers 0-9 be, and would regression work on what ever type of data it is? Also what other machine learning algorithms are best for numeric datasets.
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What type of data is needed for offset in a Poisson regression model - R

I am trying to do a Poisson regression using the following data, where infant deaths are shown per year for both North and South England. ...
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0answers
15 views

Manipulate Data Series to Produce Equal but Opposite Betas [duplicate]

Suppose I have two different series, $A$ and $B$, and perform a single-variable regression of $A$ and $B$ upon a third series, $C$, to get two betas: $Xa$ and $Xb$. Given these initial betas, I want ...
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1answer
21 views

How to use a scoring metric other than rsquared for an SVR? [closed]

I've searched through the previous questions and I can't quite find what I'm looking for. Perhaps I'm phrasing the question incorrectly, so if that's the case I do apologize in advance. I'm trying to ...
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1answer
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Is it common to maximize correlation between response variable and a combination of explanatory variables as a first model?

I am doing a linear regression project and in the exploration part I did something I was asked to explain in more detail... There are only 4 variables: 1 response variable and 3 explanatory variables. ...
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1answer
42 views

Linear regression: comparing effects between multiple (50+) groups in R

I have a dataset of 30.000+ observations. For my thesis I am investigating the effect of the weather on rating scores. For a subquestion I need to compare the effect of precipitation on the review ...
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1answer
39 views

Polynomial regression - non-constant residual variance

I have the following regression task. The dataset below is a list of costs for certain levels of a covariate variable. ...
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1answer
22 views

Degrees of freedom for error in linear regression model [if n < k]

Given a multiple linear regression model with n= 3 observations and k= 4 regressors what will be the degrees of freedom for error sum of square ?
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Removing outlier observation in panel data regression analysis

I have monthly sales data for two year at different stores of a food chain along with some other variables like number of customers, location, customer feedback etc. I am trying to build a panel data ...
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0answers
16 views

Interpretation of the intercept in a multiple logistic regression? [duplicate]

I have fitted a model by means of a multiple logistic regression, but it turns out that the only significant parameter is the intercept. Therefore, I decided to model only taking this parameter into ...
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0answers
18 views

Significance of factor variable that is an indicator for missing data

I read here and elsewhere that one technique for dealing with NAs in a database is to create a dummy variable that is 1 if an observation (row) has no missing data ...
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0answers
12 views

Formatting Panel Data [closed]

I wish to format a panel dataset that I will use to run a regression down the line... I have both individual (people) level data from survey data, as well as country level economic variables such as ...
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0answers
57 views

Binary logistic regression with brms

I've run a binary logistic regression in R, using brms. I have one independent variable (Age) and 3 dependent variables, Y1, Y2, and Y3. These dependent variables are all pass/fail tasks. For each ...
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21 views

Regression model for ML hyperparameter tuning

Problem definition: Having predictor variables such as: learning rate(continous, range 0-1), number of iterations(continous), number of hidden nodes(continous), LossFunction(categorical) and ...
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1answer
58 views

How to find the relationship between two variables using regression? [closed]

I have a Raspberry Pi hooked up to a sensor, which will send a data to the device every second. As you may have guessed, what I want is to find a relation between this independent variable time and ...
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0answers
7 views

Different levels of variability in Fixed Effects (FE) regression, no time variable

I have a dataset with 3 variables: 1) "employment growth rate 2017" by country; 2) "employee happiness (1-100) 2017" by country and occupation level. Hence the variables would be: 1. country 2. ...
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0answers
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Explanatory variable independent of the response, yet has non-zero beta

My intuition was that if an explanatory variable is independent of the response then in a multiple regression it should have a $\beta$ of zero. Consider however the following very simple example: the ...
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0answers
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Machine learning: is the effect of one predictor adjusted for the others?

In machine learning - notably ensemble methods such as random forest, gradient boosting, extreme gradient boosting etc - can we say that the effect obtained for one predictor is ADJUSTED for all other ...
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0answers
10 views

Non-Panel Fixed Effects R [closed]

I have a dataset with 3 variables: 1) "employment growth rate 2017" by country; 2) "employee happiness (1-100) 2017" by country and occupation level. Hence the variables would be: country, ...
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1answer
13 views

Predicting rank - regression or classifcation

I would like to create a rank predictor (e.g. 1-20). I'm wondering whether I should use classification or regression algorithm for that? As there is ordering between classes then it kind of makes ...
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1answer
31 views

Implementation of Shanken (1992) Adjustement for Fama MacBeth Asset Pricing Tests

I am trying to implement an unconditional asset pricing test according to the Fama & MacBeth (1973) method. The calculation of the factor-loadings as average of monthly cross-sectional regressions ...
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0answers
15 views

How to analyze time series data with very few samples for response variable

I want to use R to model a person's blood-iron level to predict how it changes over time. My response variable is blood-iron level and my explanatory variables are related to diet, use of different ...
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1answer
54 views

If the quadratic term is significant but the linear term is not, we must add the linear term to the model too?

I have a linear mixed effect model and I add the quadratic term of time in my model and it was significant and improve the AIC & BIC of the model, but the problem is that the linear term of time ...
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0answers
9 views

Computing marginal probability and Bayes factor of structural model

I have a Bayesian structural model of the following format: $Y1 = X \alpha +\epsilon$ $Y2 = S \beta + \eta $ $\epsilon = \gamma \eta + \chi $ where Y1 and Y2 are linked by the error terms. I ...
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0answers
10 views

Analyzing Data for multiple treatment groups

I'm currently designing a research proposal to analyse the effect of varying the amount of cash transfered in a conditional cash transfer program on raising school attendance rates. The cash ...
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1answer
31 views

Baseline hazard function is the hazard function obtained when all covariates are set to zero

I am trying to learn Cox proportional hazard model but I have hit a wall with the basehaz function. Lets suppose for example I have some data that I want to use ...