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.
0
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0answers
9 views
Errorbars for the intersection point of two regression lines [duplicate]
Let's say I have two sets of data and I've fit lines $l_1$ and $l_2$ to each of them. Each line has its own coefficients that have their own confidence intervals. How can I derive the errorbars for ...
0
votes
1answer
36 views
Relative importance of multiple correlated independent variables in logistic regression
I have a multiple logistic regression with 11 independent variables (x1 to x11). I have another 4 continuous IVs that are highly correlated with each other and correlated with x11. The 4 IVs along ...
1
vote
1answer
30 views
Controlling for categorical variables when generating logistic regression elasticity curve
Assume we have a multiple logistic regression model with 3 continuous independent variables (x1,x2,x3).
I understand that if we want to create an elasticity curve for a continuous variable of ...
1
vote
0answers
15 views
Measure of goodness of fit of ellipsoid model to data
Consider a measurement $m$ of a physical property, the value of which depends on the direction investigated. If the property derives from the application of a second-rank symmetric tensor, the ...
0
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0answers
13 views
low regression coefficient [closed]
I was replicating a study. All the variables have similar descriptive statistics(mean, median, std, q1, q3). However, when I ran regressions using these variables, the regression coefficients are much ...
1
vote
0answers
24 views
Test equality between coefficients in STATA
I have a very basic question. I use two equations:
\begin{equation}
y_{it}=\beta*X_{it}+\theta*C_{it}+
\sigma_{i}+\tau_{t}+\epsilon_1 \\
z_{it}=\omega*X_{it}+\sigma*C_{it}+
\lambda_{i}+\gamma_{t}+\...
1
vote
0answers
19 views
How to compare R-squared between two regression models derived from unequal sample sizes?
I estimated the variance in an outcome variable (y) that is explained by a predictor variable (x) after adjusting for the three covariates (c1, c2 and c3).
I derived a full model (y~x+c1+c2) and a ...
3
votes
1answer
77 views
Interpreting non-significant regression coefficients
Out of seven, six of the independent variables (predictors) are not significant ($p>0.05$), but their correlation values are small to moderate. Moreover, the $p$-value of the regression itself is ...
2
votes
1answer
31 views
Does regularization in regression help with numerics when the data matrix is not full rank?
I am trying to get some intuition around regression when the data matrix $A$ is not full rank in the following regression/least squares problem:
$$y=Ax+b$$
where $y \in \mathbb{R}^n$, $A \in \mathbb{...
2
votes
0answers
28 views
Why does centering the regressor at a nonzero value improve performance? [closed]
I'm trying to understand why centering myregressor at a nonzero value improves the performance.
I always thought that the variance of the feature, and its correlation with the labels, would affect ...
1
vote
2answers
26 views
How to interpret multiple regression coefficients [duplicate]
I'm running multiple linear regression with 6 variables. For one of the variables D, the correlation coefficient between D and the response Y is - 0.34. But in the regression output, the coefficient ...
0
votes
0answers
21 views
Trying to Forecast Sales using Regression (open to suggestions) and Nielsen Facts
I'm trying to forecast out sales in 2019 using significant independent variables, however these are mostly, if not all, unknown.
The method I'm currently using is to use excel "forecast" function to ...
0
votes
0answers
21 views
Deriving variance of the regression coefficient [duplicate]
I am after some help with this variance of regression coefficient derivation problem. Have already had a look at a similar question, posted a while ago but this one is slightly different. Am a novice ...
0
votes
0answers
10 views
How to calculate unstandardized estimate to quantify effect on dependent variable in percentage
Based on the path estimate from Structural Equation Modeling in a scholarly text, I would like to state that an x% increase of Variable1 leads to y% increase in Variable2 - I know that this is not ...
0
votes
0answers
20 views
Ratio estimation vs. regression analysis
I would like to know under which assumptions you would prefer one concept to the other.
I would like to conduct an analysis of the relation between sales and expenditures in a sample of financial ...
2
votes
1answer
29 views
Negative intercept in negative binomial regression , what is wrong with my model/data?
I am running a negative binomial regression using statsmodels on Python.
My DV is count data and zero-inflated. The one IV in my model is categorical and I have no constant term, and my understanding ...
1
vote
0answers
30 views
Determining the uncertainty in regression parameters
I want to regress crop yield against total rainfall collected over many years.
For each year, rainfall could be computed for different time periods i.e. total rainfall can be calculated
between 1st ...
2
votes
1answer
33 views
Linear Regression: Why do the coefficients change on the original IVs when you interact them, and add that new interacted-variable to the model?
Basically I want to know how the 'constant' value differs in each of the following models:
Model 1:
DV=income; IV1=gender (0=male, 1=female); IV2=location (0=east, 1=west)
Here, I understand the ...
0
votes
0answers
10 views
Discrepancy between coefficients generated by cv.glmnet() and glmnet()?
I noticed small differences between the coefficients generated by cv.glmnet() and glmnet() when the same lambda was applied. I am wondering why this happens.
Codes below will reproduce the phenomenon ...
1
vote
0answers
31 views
Price Elasticity Estimation with a non-linear price schedule
How do I estimate price elasticity in a non-linear price setting? Non-linear prices are seen in utilities (electricity, water etc.) where the price per unit is determined by quantity purchased.
So a ...
1
vote
1answer
60 views
lm() coefficients don't match lmer() fixed effects
I'm new to hierarchical models and am learning to use the lme4 package. My understanding is that the fixed effects generated from the lmer() function are suppose to match the coefficients from lm(). ...
0
votes
1answer
38 views
Derivation of t-statistic and p value of Regression coefficient
I had this question at the back of my mind for a while. Consider any data for linear regression problem. Optimization algorithm calculates the coefficients of each feature and stops when cost function ...
0
votes
0answers
23 views
testing Betas in different steps of the same regression analysis
I am looking for a procedure to test for a significant difference in the beta coefficient for a given predictor at one step of a regression model versus another step.
That is: if, say, at step 1 ...
0
votes
3answers
75 views
How to report negative binomial regression results from R
I have fit a negative binomial model in R, and would like to report the findings, but I'm unsure how (or if) I should convert the estimates to reportable coefficients. Here is my output:
...
0
votes
1answer
30 views
How to express the estimation result
I would like to ask you how to express the following regression analysis.
$Y=a+bX+cZ+u$
I want to mention that $b$ is significant.
In this case, which sentence in the following correct?
(1) The ...
0
votes
0answers
31 views
Comparison of nested regression models vs predictor's significance within model
I am building regression models to evaluate the effect of several characteristics of genetic variants (my predictors) on a handful of phenotypic parameters (continuous and binary - hence I am building ...
1
vote
1answer
55 views
In what instance would r, R, and β be the same? [closed]
I understand that r tells us the strength of the linear relationship between two variables, R shows how closely two variables, and β shows which dependent variables would change if we change the ...
0
votes
0answers
17 views
Quantify the uncertainties around the regression parameters
I need some advise of how to quantify the uncertainties around the regression estimates.
I have collected crop yield data across multiple locations and multiple years.
The crop broader cultivation ...
0
votes
0answers
20 views
Interpreting the Evaluation Model for Decision Forest Tree
I am working on a project to find Productivity of a person in near future and i am using Decision Forest Tree in Azure Machine Learning studio. I have a good amount of sample data (5459 rows) & 9 ...
1
vote
0answers
31 views
Interpreting linear regression results in SPSS
I am using linear regression to look at the relationship between some variables using SPSS but I'm having trouble understanding the results:
In the table of coefficients, I know most of the rows ...
1
vote
0answers
23 views
How to conduct a moderated multiple regression with two (or more) moderators?
I've been trying for a while to understand how to perform this type of analysis, but I can't seem to find any literature or even forum posts about it, so any help or guidance anybody can offer would ...
1
vote
0answers
24 views
how can I obtain a beta value for three way interaction term in a logistic regression
I am using the RMS package in R to conduct a logistic regression that contains a three-way interaction. As part of my modelling approach, I have conducted chunk tests of the interaction (using Wald ...
0
votes
2answers
25 views
Anti-logging coefficients of a regression with log-transformed outcome variable yields confusing estimates
I am testing whether self-reported days' use of illicit cannabis in the previous 28-day period predicts levels of a cannabis metabolite measured in participants' urine. There are four 4-week periods, ...
0
votes
0answers
24 views
Likert Scale for Linear Regression vs Ordinal Logistic Regression - R Square Interpretation
I'm fitting a response variable that assume values between 1 (Very Dissatisfied), 2 ,3 ,4 and 5 (Very Satisfied). My explanatory variable assumes also values between 1 and 5, in other words, dependent ...
0
votes
0answers
30 views
Extracting latent variable from multivariate linear model, based on residuals
I need some help with some basic regression method. Let's say that we have a tri-variate linear model with continuous variables (as dependent and as independent).
$$y=\beta_0+\beta_1 x_1+\beta_2 x^*...
0
votes
0answers
22 views
Derive p value from t distribution [duplicate]
I have difficulty of understanding p-value from
An Introduction to Statistical Learning by Gareth James • Daniela Witten • Trevor Hastie
Robert Tibshirani (2015) : 67
Consider simple linear ...
3
votes
1answer
45 views
Regression: Is it problematic to include a predictor when the outcome variable is based on it?
My question is based on the following discussion we often see when people try to model citation counts for research articles.
The outcome variable is citation counts for an article and some typical ...
3
votes
2answers
68 views
Standardization and explanatory variables of different domains in Multiple Regression
There's many questions on related topics but I have been unable to find one that precisely answers my question.
Let's say I'm performing a regression on multiple predictor variables $x_1...x_n$ for ...
4
votes
1answer
91 views
Why do descriptive statistics contradict with regression coefficents?
I am estimating a binary logistic regression with L1 norm. According to the regression coefficients, the sign of x1's ...
0
votes
0answers
15 views
Interpretation and presentation of coefficients for continuous variables in poLCA
I am analysing data on symptoms, signs, and autopsy findings (a set of binary Y/N variables), viral serology, for several viruses, and a few other covariates (Age, gender, site) in pigs. After some ...
1
vote
0answers
12 views
Cluster points in regression
I am trying to cluster data for a regression problem and wonder if I am way off in my approach or if there is something in it.
Problem: make a model of impact of variable L1 and L2 in Output. Output ...
3
votes
1answer
45 views
How can a variable have a positive association through logistic regression, yet a negative association through Cox regression?
I am undertaking some medical research using R.
My outcome of interest is mortality in the intensive care unit.
Data
My data looks like this (there are ~15,000 rows).
...
0
votes
0answers
8 views
Checking for change in significance of regression coefficient after adding covariate
I'm wondering whether there is a way to check whether a coefficient in a linear mixed effects model changed significantly after introducing a new variable. I have two models:
...
0
votes
0answers
10 views
Why do some attributes show null outcomes in multiple linear regression [duplicate]
I am trying to analyze this data by linear regression and found experimental outcomes given below:
...
1
vote
1answer
46 views
What explains a sudden change in the magnitude of logistic regression coefficients when increasing the sample size
Last week my team and I discovered a strange phenomenon with the coefficients of a logistic regression (LR). As we included more samples from a static dataset, the magnitude of the coefficients of the ...
2
votes
1answer
33 views
Interpretation of regression coefficients with different subsets of independent variables
I have a multiple regression problem. Let's say there is a physical system with a true model:
$$
y = b_0x_0 + b_1x_1 + b_2x_2 \;\;\;\;\;\;\;\;\;\; (1)
$$
Now, imagine I only have access to a ...
2
votes
1answer
26 views
How can I look for correlations between variables with large deviations?
I'm researching the correlation between the magnitude (a measure of brightness) and redshift ($z$ - a measure of distance) for a variety of galaxies called quasars. Plotting the magnitude against $log(...
1
vote
0answers
12 views
How to quantify SKU growth by removing the effect of price?
I am having Price ($/litre) and volume (litres) sold information at a Brand and also at a SKU level by weeks. I am looking to find out the SKU brand trajectory/growth by removing the effect of price.
...
1
vote
1answer
34 views
How to test the equality of coefficients in a quantile regression?
I run this model on the 95th percentile (Stata 14)
...
0
votes
0answers
6 views
testing the null hypothesis that two coefficients are equivalent (LR)
I'm running a replication study on Livingston's (2005) examination of reputational effect on online auctions. sellers are divided into dummy quartiles based on their feedback scores. I have run a ...
