The parameters of a regression model.

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9 views

Coefficient with df=0 in log-binomial model

I am using log-binomial modeling in SAS to model the PR of my outcome given exposure directly since the prevalence is >10% so the OR~PR approximation doesn't hold. Most of my models have converged ...
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1answer
23 views

Interpretation of coefficient in log-linear model with share predictor

There are several questions on the interpretation of coefficients in log-linear models such as Interpreting regression coefficients of log(y+1) transformed responses Log linear model interpretation - ...
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36 views

Sampling Distribution (Variance) of Weight Estimates

I am currently facing an issue regarding the sampling distribution of weight estimates. Problem Statement Given an estimate of a $n \times n$ covariance matrix $\hat{\Sigma}$ of $n$ random variables ...
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24 views

Getting the wrong sign [duplicate]

In a regression, when you get negative coefficient which you know should be positive, why it is necessary to include possible omitted variable that is likely to have positive coefficient and ...
3
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1answer
47 views

What is the correct way to determine which features most contributed to the prediction of a given input vector?

I am using logistic regression for binary classification. I have a big data set (happens to be highly unbalanced: 19 : 1). So I use scikit-learn's ...
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21 views

Promotion analysis with regression, negative coefficients

I used multiple linear regression to model promotion effects on sales on sample retail store, but some coefficients becomes negative. As a business interpretation, should I consider these promotions ...
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26 views

Combining estimates from multiple regressions

I am interested in using quantile regression to fit the following model at different quantiles of a response variable: (1) y = b0 + b1*g1 + b2*g2 + B*Z where b0 is an intercept, g1 and g2 are dummy ...
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1answer
23 views

Comparison of coefficients within one regression

I am running a multiple regression model based on panel data that investigates the effect of different types of firm ownership on a certain dependent variable (OLS-estimators). The two independent ...
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10 views

How to Test Collinearity Between GROUPS of Predictors?

I had a model (made with VW, log loss) based on a set of base (p=1000's) predictors. It did not predict well. I added set A of predictors (p=~5 predictors), and it improved immensely. I added set B ...
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28 views

Time varying coefficient in cox model

I have a model for survival after an injury that is borderline passing the Schoenfeld test for the proportional hazards assumption (cox.zph() in R). However, ...
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10 views

Significance test for multiplied coefficients using STATA [closed]

A two stage model is used because Y is a function of C and C is a function of M theoretically. i.e. Y=F(C(M)). We want to find the effect of M on Y. If I estimated the two-stage model by 2 stages ...
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9 views

coefficients in cumulative link models

I used ordinal package to build a cumulative link model: require(ordinal,quietly=TRUE) fm1 <- clm(base ~ . , data = df_reg) summary(fm1) df_reg is a dataset ...
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1answer
29 views

Backtransforming the vertex of a quadratic function

I have created a model for which it was necessary to scale my predictor values by subtracting by the mean and dividing by the standard deviation of the X values. This resulted in variables centered ...
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1answer
27 views

Interpreting multiple polynomial regression coefficients

I read a couple post on interpreting polynomial coefficients here in cross validate however none of them touch on how to interpret multiple polynomial regression coefficients. Perhaps its the same but ...
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1answer
30 views

How does one extract the final equation from glm poisson model?

I have a Poisson model that is performing well. Now we need to put it into Java code and release it to the world. What is the equation that I plug the Poisson coefficients into? Similar to this ...
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1answer
27 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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28 views

Contingency table model

Calculate the two regression coefficients and hence obtain the two regression lines from the following data I can find the two regression lines by using the equation y=b0 + b1x for ungrouped data. ...
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2answers
39 views

Logistic regression on all data in order to analyze predictors

I have some experience working with classification, and in those instances we always use a training and a test set (and possibly validation sets). However, I'm currently facing a different problem. I ...
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2answers
93 views

modeling prices with the Hedonic regression

I'm using the concept of Hedonic regression in order to model the prices for real estates. I'm having some trouble with my approach. What I have and what I do my data consists out of real estates ...
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23 views

Ranking the performance of countries (entities) from a panel-based fixed effects regression

I am performing a fixed effects regression analysis on countries, $i$, over a time period $t$ with regressor $X$ and outcome $y$ so that the equation is $y = \beta_0 + \beta_1 X_{it} + \epsilon_{it}$ ...
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31 views

regression with constraints on coefficients in R returns bad results

I used the method pcls in order to make a simple regression (price ~ livingArea) with constraints. I set the constraint for ...
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1answer
41 views

Confidence intervals of coefficients of multiple regression

With following model of mpg vs other variables in mtcars dataset: ...
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1answer
25 views

Using standardized coefficients for relative importance with factor predictors

I have following dataset which is modified from birthwt dataset of MASS. ...
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34 views

Regression and ANOVA of factors

I am doing research on automated banking service quality. In my work I have found in total 6 dimensions (factors): 4 service quality (SQ) factors, 1 customer satisfaction (CS) factor and 1 loyalty ...
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2answers
75 views

Which standard deviation to use for p-value of regression coefficients?

Matlab generates regression coefficients for vector time series models ("vgxvarx"). For a given regression coefficient, the p-value is just the area under the t-distribution beyond |t| > ...
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22 views

Insignificant slope coefficients

While calculating the value of the dependent variable why do we take into account even the variable whose slope coefficients were not significantly different than zero? Is my understanding correct ...
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14 views

Why would standardized betas be high (e.g. .66) but non-significant in moderated regression?

Running a moderated regression using PROCESS macro in SPSS (issue replicated by running the same moderation using mean-centered variables in SPSS linear regression command box), I am finding that the ...
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1answer
36 views

How to interpret two observations that are otherwise identical in a regression model

I am confused trying to interpret how two observations are otherwise identical but differ by a dummy variable. For example if we have the following model with a factor variable race being White race ...
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1answer
28 views

How to deal with missing coefficients while bootstrapping regressions

I'm using R boot() function to perform regression bootstrapping. When boot() resamples my data, can happen that some coefficients are missing, especially in the case of factor variables with many ...
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2answers
34 views

Evaluating a factor variable

I am seeking feedback on the theoretical appropriateness of two approaches I am planning to follow. I have a dependent continuous variable (y) and several independent variables some of which are ...
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1answer
22 views

Groupwise contribution to regression coefficient?

My intution tells me that the following is a straight forward question, but I could not find relevant answers when I searched for it. I assume the reason for that is that I don't know the relevant ...
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15 views

Overlap between 1) regression results and 2) correlation between residualized versions of variables

Scenario: 1) Regress a standardized variable A ("stand. A") on a standardized Variable B "(stand. B"). Since both Variable A and Variable B have a number of potentially confounding influences on ...
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1answer
60 views

Significance of individual coefficients vs Significance of both

This was a question I read from google quantitative analyst interview on glassdoor: If each of the two coefficient estimates in a regression model is statistically significant, do you expect the test ...
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18 views

I did ridge regression and i am confused with coefficients

ridd=lm.ridge(mariner~o1+o2+o3,q,lambda=0.001) ridd o1 o2 o3 34.7597607381 0.0001989008 0.0393011905 ...
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31 views

Interpretation and meaningfulness of regression coefficients

I have performed logistic regression on banking data which is trying to predict the bad customers correctly due to the cost involved. I have build a model and pasting a picture of the output obtained ...
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1answer
60 views

interpreting coefficient values in lasso regression

I am running a lasso regression function. I have about 45 features and I am predicting 1 dependent variable. After running lasso regression I get the coefficient values of the features. 1.If I look ...
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1answer
46 views

Why does the amplitude, bandwidth and position of Gaussian change when data changes from positive to negative

I'm trying to fit a single Gaussian to some values in Matlab. When the values are positive, the model fits without any issues. However, when these values become negative, the r squared value changes, ...
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1answer
10 views

How to test that two covariates have the same impact on dependent variable?

Given the model $y =\beta_0 + \beta_1 x_1 + \beta_2 x_2 + u $ where $x_1$ and $x_2$ have completely different scales and units, is it possible to test whether their impact on $y$ is the same? i.e. ...
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1answer
59 views

High R-squared although many insignificant coefficients

I just did a regression based on the gravity model where I try to identify the most important factors that determine the trade flows. In total I have 18 variables and 363 observations. In fact I would ...
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1answer
20 views

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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1answer
31 views

Inconsistent Performance of PCA Results from SPSS

I've completed PCA with my dataset (16 variables) and extracted 3 factors. I then created an Excel spreadsheet where I can enter in user provided data and calculate the scores for each of the three ...
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1answer
42 views

How to check for confounding factors

I have been doing an analysis using a difference in difference setup. In my raw sample I use OLS and first difference (two time-periods) and I get the effect that I would expect. Namely that shocks in ...
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24 views

Is the constant value ignorable?

I am running a linear regression on SPSS. Basically I have 2 independent and 1 dependent variables; and I would like to understand which of my independent variable is more effective on the dependent ...
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20 views

Unit weighting for linear composites / regression

Cohen (1990) mentions a regression that I have not heard about before. Here is how I understand his description: Standardize the dependent and the independent variables Regress the standardized ...
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1answer
85 views

Large value of exp (B) in binary logistic regression SPSS what is wrong? [duplicate]

I had a very large value for Exp(B) in SPSS binary logistic regression. What is wrong and what should I do?
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1answer
50 views

Equation of a fitted smooth spline and its analytical derivative

I need to fit a spline function to a data set. I tried with bs, ns and smooth.spline. In my ...
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1answer
33 views

Beta coefficient interpretion with categorical and continuous predictors in a linear regression

I am trying to run a linear regression with both categorical and continuous predictors. I have coded the categorical predictor (with three levels) into three dummy variables, and entered the two dummy ...
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13 views

Covariance of the regression coefficient of two regression given the correlation between the independent variables

Given the following equations $$ Y=x_1\beta_1+\epsilon_1 $$ $$ Y=x_2\beta_2+\epsilon_2 $$ Where $Y$, $x_1$ and $x_2$ are all normalized, and that $x_1$ and $x_2$ are correlated with Pearson ...
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1answer
127 views

Trust of coefficients of Logistic Regression

I use logistic regression to model the probability of an event and all of my features are categorical variables. Note that some values of the categorical variables are more frequent than others. The ...
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35 views

Counter intuitive result from logistic regression

I am looking at how well test scores can predict disease status (case/control). There are 6 tests total, A, B, C, D, E, F. And for tests A-E, a higher score is worse (i.e, a higher score is associated ...