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.

Filter by
Sorted by
Tagged with
0
votes
0answers
48 views

The variance of a biased estimator

This builds on an an earlier question from Math SE. I am just starting to learn about the simple regression model. In particular, I am trying to understand what happens to $\hat{\beta_1}$ when the $E(...
0
votes
0answers
479 views

AIC in R: Back-transformation of model averaged coefficient estimates

I am running an analysis using a mixed model with lmer in R. I am using AIC as my model selection process. I have a global model and am including within the selection process all subset models ...
0
votes
1answer
121 views

What is the best way to quantify the goodness of fit between the data and my model?

I am modeling the total fluid rate at the bottom of an oil well using a roughly exponential model (mixed with other terms representing an input signal). Here is one example (blue circles are the ...
0
votes
2answers
243 views

DLNM and crossreduce(): getting the coefficients behind the cross-basis

I am using the R package dlnm to fit a distributed lag non-linear model estimated with lm(). One can specify both the exposure ...
0
votes
0answers
216 views

Testing the equality of Beta Estimates from Multiple (>2) Quantiles in Quantile Regression

I'm trying to determine whether Beta estimates at different quantiles obtained using quantile regression (quantreg package in R) are statistically different from ...
0
votes
1answer
110 views
0
votes
1answer
137 views

Correct interpretation of linear coeffs for 1 interaction, 1 numeric, 1 categorical

Good day, XValidators. This is my 1st question in the community. I'm at my wit's end here. Nowhere in the interwebz nor in youtoubeland can I find an answer to the following: Assume you have this ...
0
votes
0answers
217 views

Comparing regression coefficients using F-test to assess for batch effects

Here's what I have: two datasets with ~27,000 variables (same variables for each dataset). I'm trying to test whether or not dataset1 and dataset2 display batch effects. Namely, I want to do PCA and ...
0
votes
1answer
67 views

Size of Regression Coefficients

I have run a probit regression and the size of my coefficients seem to be quite big with respect to other similar studies. For example, 0.254 vs 1.207 - does this mean anything in particular or is it ...
0
votes
0answers
56 views

Normalization/Multiple Regression Question

I work in cell culture and normally don't have to use anything more than T-tests, but this project has me stumped... The study design: 1 control treatment and 7 experimental treatments with one ...
0
votes
0answers
90 views

Using predicted variable among interaction predictors in R

I'm trying to build a model in order to predict a certain variable using the following model: ...
0
votes
0answers
161 views

R syntax - Multivariate regression with an unknown coefficient or two, for a dummy (engineer)

Something I rather vaguely asked a few months back, saw the tumbleweed roll by (actually hacked some hardware in the time, to get a few answers) before the question was deleted, so I'll try again on a ...
0
votes
0answers
17 views

Which way of regression modelling is correct among below options, when the predictor is a product term? [duplicate]

I am modeling a response Y against a predictor X, which is a product of two variables X1 and X2. I am interested in the coefficient of X. Mathematically which way of modeling is correct?: Y ~ X Y ~ ...
0
votes
0answers
108 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 ...
0
votes
0answers
43 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 ...
0
votes
0answers
270 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 ...
0
votes
1answer
416 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 ...
0
votes
1answer
96 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 ...
0
votes
0answers
34 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 -1....
0
votes
1answer
32 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. ...
0
votes
1answer
109 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 ...
0
votes
0answers
36 views

Is the constant value ignorable? [duplicate]

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 ...
0
votes
0answers
187 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 ...
0
votes
0answers
62 views

Standardized Coefficients and Partial r

Ive looked over a few of the posts here on regression coefficients and partial regression coefficients but haven't seen an answer to this question, which maybe easily inferred from the other answers ...
0
votes
0answers
258 views

Worryingly Huge Coefficients with Regression Discontinuity Design

I am running a regression discontinuity design for a project in the early stages. I'm unable to share the data or printouts at this point, for which I apologize, but hopefully the general issue I'm ...
0
votes
0answers
64 views

Different coefficients of linear discriminants with the same raw data

I have just tried two ways to perform a linear discriminant analysis. Mode 1 This is the data, divided in two tables (printed from screen using R commander): They belong respectively to the two ...
0
votes
0answers
1k views

Percent change interpretation in log-transformed regression: Percent change from what?

I am dealing with a regression model where both the DV and IV are log-transformed. I have found this explanation of how to interpret the effects (both in the Cross-Validated hyperlink and in ...
0
votes
1answer
141 views

oaxaca decomposition: how to treat error term and do intercrossing intercepts matter

I am just wondering if I can decompose a difference in earnings let's say between year 1999 and 2002 into the difference due to a higher education level of labour market participants and due to higher ...
0
votes
1answer
60 views

What to make of countervailing spatial regression coefficients?

I am running regressions across a country's counties (N about 300). I divide the country in two regions A and B to control for potential unobservables. My explanatory variable varies at the county ...
0
votes
0answers
570 views

Standardized Coefficient (beta)

I am doing research on advanced manufacturing technologies such as Computer Aided Design, Computer Numerical Machines and Computer Aided Engineering. When I found their Standardized Coefficient (beta)...
0
votes
1answer
44 views

Comparing effects of different methods when each method has multiple levels

I'm working in retail and we are trying to determine the effect (on units sold) of reducing an expense for a set of products within a product group. We have two methods of reaching this goal. One is ...
0
votes
2answers
141 views

Regression coefficients significance

What are theoretical reasons to keep variables which coefficients are not significant? I have several coefficients with p > 0.05. What's causing large p values?
0
votes
0answers
62 views

How can I create a linear regression model with some negative coefficients in R? [duplicate]

What I'm trying to do is to construct a linear model in a form like $$ Y = \beta_0X_0-\beta_1X_1+\beta_2X_2 + \beta_3 $$ where $\beta_0$, $\beta_1$ and $\beta_2$ are coefficient of predictors $X_0$, ...
0
votes
0answers
31 views

ARIMA, p and q identification. Please help [duplicate]

I am very new to SARIMA and I am really facing a poblem which p,q,P,Q to use. Here is ACF and PACF of first-difference, two first plots (stationary) and ACF and PACF of first-seasonal difference (two ...
0
votes
1answer
71 views

why is there a huge difference existed in coefficient of determination obtained from 10-fold cross validation?

I'm using gradient boosting regression model (GBRT). To evaluate this model, I use 10-fold cross validation, in each of which I set same param and compute the coefficient of determination as a ...
0
votes
0answers
656 views

How to set up the initial data in the nls model

I am struggling with nls model given below. I have a blur idea how to set up the initial values in it. Shall I use "try and error" method or is there any other way to make it more systematic. ...
0
votes
2answers
56 views

Model regression of means different size and variance

I want to explain the relation between getting a reply and posting in a e-commerce. I want to know how much a reply increases postings. I know I could do a regression of postings=f(replies) but the ...
0
votes
0answers
89 views

Estimate linear regression using items randomly selected from an item pool

I am asking this question against the background of a linear regression with single predicted variable $Y$ and multiple predictors $X$. $X$ comes from a survey using an "item pool" which suggests that ...
0
votes
1answer
54 views

Understanding Regression vs. Means/Median Results

I am having a little difficulty understanding my results - could someone help me understand how to interpret, and if my process is sensible? Here is an example of what I am doing I am trying to ...
0
votes
1answer
70 views

Interpretation of two indexes Interaction Term

Respected Fellows. I will thankful if someone help me to explain my model results.my model is as follows. Yit=αPFit+βPSit+δ (PF*PS) it+εit Where Y is GDP per capita PF=Political Freedom Index ranges ...
0
votes
0answers
157 views

Interpretation of Linear SVM Coefficients [duplicate]

I’m building a model using Linear SVM from the Scikit-learn package in Python. I have found that Linear SVM performs much better on my training set than Logistic Regression. My question is, is there ...
0
votes
0answers
285 views

Compare regression coefficients within one sample

I run two univariate linear regressions within one sample (same subjects, two different conditions). Now I would like to know how to compare the regression coefficients in order to find out whether ...
0
votes
1answer
111 views

Discrepancy between coefficient and mean difference in predicted values of logistic regression

I'm using a poisson-binominal logsitic regression model to analyze a list experiment (item count technique) where the outcome variable is a binary response of the respondent to a sensitive item (e.g., ...
0
votes
1answer
178 views

Interpreting percentage units regressions

I am using a panel of 2249 schools with data from 2002-2008. Some of the schools are single sex schools whilst others are mixed sex. Some background on my regression: Consider the determinants of ...
0
votes
0answers
615 views

Alternative to Chow test for equality of estimates, when the data for the 1st group is not available

My goal is to compare published regression weights estimated from a sample in another country, with those of the same model established on our data.There is ample evidence on the web that a Chow test ...
0
votes
0answers
201 views

How to interpret this binomial logistic regression output in R

I have run my logistic regression model to find out whether the gender of a test name is a predictor of the gender of the word assigned to the test name. ...
0
votes
0answers
184 views

Coefficients and Standard Errors

We have a last assignment for my poli sci stat class and these two have really got me stumped. We really didn't go over multiple regression very well so if anybody can help, I appreciate it! Your ...
0
votes
0answers
1k views

Larger coefficients (economically) or flipped sign when using fixed effects instead of OLS?

Is it possible to get a larger coefficient (either a larger negative or a larger positive) when moving from OLS to a fixed effects regression? Furthermore, is it possible/likely for a coefficient ...
0
votes
0answers
150 views

How to calculate Beta and coefficient of determination ($R^2$) from unstandardized coefficients in OLS regression? [duplicate]

I have a table in which the multiple linear regression results is provided. If I have unstandardized coefficients and standard error for each independent variable, is it possible to calculate ...
0
votes
1answer
2k views

Multiplicative regression coefficient

The expected model is: $$ Y = X1*X2*X3 $$ Taking logs we should get a coefficient of $1$ on all three when we regress. That is: $$ \ln (Y) = b + b1 \ln(X1) + b2 \ln(X2) + b3 \ln(X3), \\ \text{gives: ...