Questions tagged [regression-coefficients]

The parameters of a regression model. Most commonly, the values by which the independent variables will be multiplied to get the predicted value of the dependent variable.

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4k views

Interpretation regression coefficient percentage points

I have a simple linear regression model, where the independent variable is defined in percentages (%) while the dependent variable is in percentage points (difference between two yoy %-rates). How ...
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Interaction effects and insignificant main effects - Back to basics

Imagine the following regression model: $\text{Abnormal Returns} = b0 + b1*SENT + b2*SIZE + b3*SENT*SIZE + e$ SENT is a standardized variable. SIZE is equal to 1 for "uncertain" firms, and 0 for ...
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Quantitative and categorial predictor in one model

This is what I would like to know, due to some logical problem behind! I have a model as: Crown radius = Diameter at breast height + Location DBH is quantitative, like 30cm, 40cm... Location is ...
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100 views

Interpreting what this means in a paper - significantly different at the .05 level? [duplicate]

I am having a hard time interpreting what something means in a paper I'm trying to get through. If you care, this is the paper: Gender Differences in the Effect of Education on the Slope of Experience-...
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337 views

Java and R: Least Squares Coefficient Estimation - Start at time Zero?

This is the data set I have: vector <- c( -7.459981, 13.26651, 12.10128, 2.380662, 26.42393) Doing an estimation of the coefficient with a linear regression ...
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659 views

Running all possible additive combinations of a linear model and averaging the coefficients

I have nine predictor variables and one response and when I run a linear model in R I'm getting negative coefficients and non-significant p-vales for essentially all the estimates. I've examined the ...
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672 views

Multiple Regression - Converting Standardized Coefficients to Unstandardized

I recently performed a multiple linear regression using a standardized set of data, and I was wondering if it possible to convert the standardized coefficients from the regression into usable ...
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1answer
174 views

Simple linear regression and sampling

I have a small dataset (60 elements) for which I fit a simple linear regression model, and obtain a small coefficient of determination ($R^2 = 3\%$). I'm a beginner in statistics so I'm trying to ...
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Positive coefficient but negative marginal effect in mlogit

Is it plausible to have a positive coefficient with a negative marginal / impact effect after running multinomial logit model?
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Imputation model: Pooled model is insignificant. How to interpret?

I have ordinal data on three IVs ranging from 1 to 5 as below: IV1: Not at all Important - Very Important IV2: Not at all Satisfied - Very Satisfied IV3: Performs much Worse - Performs much better ...
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128 views

Issues in estimation and plot

I am learning adaptive filters and testing the performance of using Least Squares and Kalman filter for parameter estimation for $y = X + \text{noise}$. The model is autoregressive AR(2) model $$y(t) ...
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117 views

Multivariate model and large regression

I am not familiar with the concept of multivariate model and just learning about regression model. I am familiar with Autoregressive model and Moving Average. Multivariate regression model provided ...
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What do the coefficients of the crossproduct of regression mean?

How can I interpret the coefficients of the crossproduct of each of the following codes? What do they mean? How can I deduce that they correspond to our expectation? Also which crossproduct is correct?...
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605 views

R Interpret coefficient from Survreg(dist=“gaussian”) [closed]

I was wondering if anyone could help me on how to interpret the coefficient from an analysis I have carried out in R (survival package). The data is right ...
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R: Explanation of a multiple linear regression summary [duplicate]

I am quite new with R and while i am able to perform the basics i am not yet able to understand the output results. For example: summary(lmodel) generates the ...
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45 views

data prediction by regression or better ways

I am working on data prediction. Given data of a random variable $X$ and $Y$, find out how to predict $Y$ from $X$. I know how to do it by linear regression, $\hat{Y} = kX + b$. But, here, $X$ is ...
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Finding an optimal value for parameter given other parameters

I am looking for a way to find an optimal value among several combinations of values. The data looks like this: ...
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1answer
67 views

Coefficients by group

I have a data set with 8 different treatments and there is unequal number of observation within each group. I'd like to calculate regression coefficients for each group but I can not do it in other ...
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How can I set a maximum and minimum level for a dependent variable?

I have to make sure that a dependent variable I explain using linear regression ranges between a minimum of 0% and a maximum of 30% (it is an investment weight in a portfolio). How should I proceed ?
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Interpretation of the regression coefficient of a proportion II

Following question: Interpretation of the regression coefficient of a proportion type independent variable In my model I have a log dependet variable. As indenpendet variables I have one proportion $...
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525 views

How do sampling error, measurement error and specification error affect regression coefficients

Can anyone answer the question or direct me to the proper resources - ESPECIALLY for sampling error effect on the coefficients? How would the coefficients be affected if the independent variables came ...
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873 views

determine the growth rate given a time series data

I have a data sets like this: ...
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339 views

Mean regression factor scores and attributes cross tabulation yields. Why are all expected signs reversed?

I ran a factor analysis on 20 reasons for purchasing 4 different goods. These are ranked on a Likert scale from 1 to 5 with 5 being "extremely important", 4 "important", etc. I extracted 4 factors ...
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726 views

How to compare regression coefficients across three FGLS models in Stata?

I have a longitudinal dataset, so for each company different year observations. The time period of the dataset is 1993 to 2008. I tested a FGLS model on the whole dataset. Now I want to test the FGLS ...
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When using Lasso and calling coefficients (.coef_) which is the coefficient of the constant? [closed]

By calling .coef on the Lasso model built, there are only numbers corresponding to the coefficients. These coefficients are supposed to match, say, the columns of the pandas dataframe given as input. ...
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Calculating Ridge Regression Coefficients in R When Using K-fold Cross Validation [closed]

I'm trying to use k-fold cross-validation in creating a ridge regression model, but I'm not exactly sure how. I'm using a code similar to the one linked here, but I can't seem to find the ...
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Variable Importance sorting by absolute value of x or fully standardized coefficient?

I am looking at the output of a linear regression model and would like to sort the IVs by feature importance. In this case I want to use the absolute value of the standardized coefficients since my ...
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How to interpret two regression lines in one figure [closed]

I am trying to interpret the intercept and slope of both lines in the following figure: When I run a summary of the linear model it gives me this result: (Intercept) ...
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1answer
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Multiple regression when the dependant variable is unmeasured or hidden

Say I was measuring the individual performance of each of a group of athletes every week. I measure things like running speed, jumping height, grip strength etc. I want to use these scores with ...
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19 views

Interpret Coefficeint as change in Percentage-point or Percentage

Having carried out the regression below, I'm struggling to determine what the correct interpretation of the predictor variable would be. Given that the dependent variable is binary, where 1=...
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1answer
19 views

What is a reason that in Lasso Regression we can force all coefficients positive & intercept =0?

I have a regression problem where I need all coefficents to be positive and the intercept to be zero. I can do this in sklearn but i don't understand how the algoritm can force this conditions through ...
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How to interpret coefficients of parametric terms in comp.risk?

I am trying to fit a flexible competing risks semiparametric regression model with the timereg package. My primary goal is to estimate the effect of Z on the cumulative incidence of the event of ...
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Interpreting the Odds Ratio of a logistic regression model

I'm currently working on building a logistic regression model with the aim of predicting whether a given stock index will go up or down the following day. The table below shows the 3 models I've ran ...
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Using the autohotencoder in PySpark for a linear regression but no reference category

I created dummy variables using the autohotencoder and as I have learned dummy variables you also need to have a reference category. However I have 7 dummy variables for the weekdays for example, so I ...
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1answer
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Regression coefficient problem

The question asks that when the case is $X_1 = 1$ (when I am an asian instead of other ethnicity, a dummy variable), then what is the value of $Y$? As the $b_1$ has a P-value much larger than $0.05$, ...
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Insignificant coefficient in a regression

To simplify the question, for example, the interception, which is Beta 0, is +500 and the predictor X1 being 1, Beta1 being negative 100 and other predictors Xi are all 0. i.e. Y = 500 -100 X1. The ...
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fitting suitable regression model to identify predictors from contingency table

so a study was conducted for some game and the probability of success of the game was noted in a contingency table. I have a 5x5 contingency table which is age group by task difficulty(split into ...
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1answer
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multiple regression coefficients - Standard error of intercept

I am implementing an R-type summary() function in python with the restriction to exclude use of scientific libraries. (assignment) I found this https://www.nd.edu/~rwilliam/stats1/x91.pdf material ...
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Significance of fixed effect coefficients in multinomial logistic regression

I am trying to do a multinomial logit regression, and I understand that the fixed effects coefficients are a bit difficult to interpret and that they can in some cases be 0 or negative but actually ...
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1answer
16 views

Slope estimator for the regression line through the origin

For a regression line through the origin with the equation: $$ \tilde{y}=\tilde{\beta_1}x $$ How did we use OLS to get the below equation? I know it is by minimising the SSR but I can't seem to work ...
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main effect significant while interaction insignificant in moderation analysis?

Please help with the following output. I have two IVs Example: (happiness IV1) (genderIV2) say on performance (Dv). question 1- I ran simple regression for happiness and performance as well as gender ...
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Impact of individual features under multi-collinearity

Assume the following scenario: I have four features: $x_1$, $x_2$, $x_3$, and $x_4$ There are non-negligible multi-collinearity among the features. I want to predict $y$ (response variable) with ...
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Removing multi-collinearity with PCA for regression analysis

I'm interested in studying the impact or importance of each feature on the response variable. I'm thinking running multiple linear regression with multiple features, and running regression analysis ...
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R quadprog for coefficient constraints

I have the model that I need to estimate, Q = B0 + B1*Q1 + B2*Q2 + B3*Q3 + B4*Q4 + B5*Q5 with the coefficients constrained to: B2 * B5 - B3 * B4 = 0; I believe I can use the quadprog package to ...
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simulate data for multiple regression based on standardized coefficients and covariance among predictors

I want to simulate data for multiple regression based on standardized coefficients (denoted $\beta^{'}$) and covariance structure among predictors. My problem is that I don't know how to determine the ...
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18 views

SpatioTemporal regression

I have a data-set containing rain value for 6 stations and station coordinates (lat,lon). I used lm function taking lat,lon,day, their interaction and rain as below: ...
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Identifying most significant variables in multiple regression

Imagine that the total cost for 100 patients undergoing the same procedure in a hospital, is further broken down into 10 cost categories (such as the surgery fees, room charges, consumables cost etc). ...
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Dealing with oversized effects in Linear Regression

I'm learning about GLMs and interpreting regression coefficients and so I'm experimenting with simulated data and pymc3. I've synthesised a dataset where X is an array of 5 normally distributed ...
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Interpretation of higher coefficient for group with smaller mean

I am running a fixed effects poisson model with robust standard errors in STATA (xtpqml). The model I run it on has my count data as dependent variable and then as my independent variable I have a ...
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Interpreting Logistic Regression Categorical Coefficients

So I have this question: If we fit a logistic regression with categorical predictor X with categories A, B and C, and have the estimated coefficients β0=−2.5 and βB=0.5 and βA=−0.2. (a) Interprete ...