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.
2
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1answer
54 views
Inclusion of standard error in regression equation
$$
\begin{alignat}{14}
P =
11&.32
&+ 0&.71 \,\text{PASN}
&+ 1&.54 \,\text{DIS}
&- 1&.02 \,\text{DIS}^2
&+ 3&.44 \,\text{FUEL}
&+ 1&.36 \,\text{FIRST}
&...
0
votes
1answer
25 views
Coefficient Interpretation when dependent and independent variables are percentages
I have built a linear mixed regression model with fund returns (measured in percentage ie. 0.01 denotes one percent) as the dependent variable. For the independent variables I have percentage level of ...
1
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0answers
16 views
What is the effect of balanced class weights on logistic regression coefficients?
I'm specifically using sklearn's LogisticRegression on my unbalanced dataset, which has around 97% negative responses and 3% ...
-2
votes
0answers
17 views
correlation coefficient [on hold]
Based on the data in the table above:
I just need someone to confirm my answers. I did the question in MATLAB.
a) Find the correlation coefficient between hydrocarbon levels and oxygen purity
The ...
3
votes
1answer
44 views
How to test whether individual fits to regression line or not
I have a defined regression model for the healthy control (HC) group, with corresponding CIs of coefficients and of E(Y).
I would like to test whether individuals belonging to another population (...
1
vote
1answer
34 views
Interpretation of removed continuous variables in regression due to linear dependence
I have created a standard OLS regression model to estimate the House Price and one group of variables describe the age group percentage of population in a particular neighborhood (ranging 0 to 100).
...
0
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0answers
7 views
Obtaining Mean Differences from DESeq2 Output
I have conducted some analyses using DESeq2 and obtained the output. However, instead of interpreting the effect sizes as log2FoldChanges, we would prefer to obtain a model-based mean difference.
I ...
1
vote
0answers
35 views
Is the Coefficient of Variation valid for data which does not follow a normal distribution?
I am trying to compare the dispersion of several data vectors. As an example I have that via two methods produces one vector of data that fits a normal distribution and other one that follows an ...
1
vote
1answer
42 views
How to calculate the coefficient of a dummy variable reference category?
I am currently building a regression model with numerous continuous, categorical (employing dummies) and interaction variables. I understand we must use k-1 dummies with one variable becoming the ...
0
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0answers
20 views
interpretation of coefficients of independent variables in fractions
I am a bachelor student finishing my thesis and desperately need some help with the interpretation of regression coefficients. I am currently quite confused and my deadline is three days away. I have ...
3
votes
1answer
73 views
Interpretation of standardized (z-score rescaled) linear model coefficients
I have analyzed some data on vegetation change as a function of change in soil parameters. I compared a dataset from 2001 with a dataset from 2018 (fully balanced).
To investigate the change in ...
0
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1answer
41 views
ANOVA is significant but coefficients aren't
My master thesis investigates the relation between stock raw returns and sentiment scores.
To make a conclusion there is a multiple linear regression with the mean sentiment, the variance of the ...
0
votes
0answers
9 views
Multiple regression and multiple comparisons 3 groups
I'm trying to compare the effect of an IV on my DV, where my data are separated into 3 groups. Specifically, in one group there is a significant correlation between IV and DV, but in the other two ...
0
votes
1answer
18 views
regression with very low R2, metric coefficient interpretation
my regression model give extremely low R2. In this case can i still interpret my X variables with significant p-value in the way that x goes up by 1 unit, y goes up by coefficient unit (with others ...
0
votes
1answer
42 views
Log-linear difference-in-differences
I am estimating several linear models using a difference-in-differences (DiD) framework. The model interacts a treatment indicator (i.e., 1 for the treatment group, 0 for the control group) and a "...
0
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0answers
20 views
Elastic Net - number of non-zero variables
I have a question regarding the interpretation of the trace of coefficients when running Elastic net with the package glmnet in R.
This is the plot I obtain with alpha = 0.5
My understanding is that ...
2
votes
1answer
62 views
Updating regression solutions for a new regressor without the original dependent variable
Note: This question is analagous to the question I asked here except instead of a removing column, I am adding it.
I am interested in a linear regression on the model;
$Y= X\beta + \epsilon$
And I ...
0
votes
0answers
13 views
how to report paired comparisons in linear basis function model?
I am struggling with correctly reporting the results of a linear (mixed) basis function model I ran. The model is specified in R as
...
1
vote
1answer
18 views
Ceteris Paribus interpretation if it isn't possible in reality
Does it make sense to include both respondent's age (in years) and respondent's partner's age (in years) in a simple linear regression with cross-sectional data? The outcome variable, for example, ...
1
vote
1answer
31 views
OLS loss function 3-d surface plot
I was trying to plot the OLS loss function as a function of coefficients $\beta_0$, $\beta_1$. As far as I know it should be a convex function with one local minimum which is also a global minimum.
I'...
0
votes
0answers
29 views
Will LASSO choose variables that are highly correlated with the outcome variable?
Suppose we have access to an outcome variable $Y_i$ and a $p$-dimensional vector $X_i$ for $i=1,\ldots,N$. We run a LASSO regression of $Y$ on $X$ for every penalty/shrinkage parameter $\lambda$ in an ...
0
votes
0answers
8 views
Error estimates for coefficients of a non-negative quantile regression
I am looking for a way to provide an error estimate for coefficients obtained from a non-negative quantile regression. The complicated part aside from positivity constraints is that my observations ...
0
votes
1answer
15 views
Corroborating a differnce in differences identification strategy
I read in Mostly harmless econometrics that a good way of testing whether a difference in differences is a good identification strategy is running this equation:
where the first sums are post-...
0
votes
2answers
53 views
Validity assessment of multiple regression marketing mix model
My employer has engaged a consultancy firm to carry out marketing mix modeling in order to quantify the impact of various marketing activities and promotional campaigns on overall sales and also for ...
3
votes
1answer
60 views
Intercept in demeaned and rescaled regression model
Suppose I have a linear model;
$Y=X\beta+\epsilon$
Where $X$ is $(n \times p)$, with the first column of $X$ being an intercept column (consisting only of ones). Now suppose I construct $\tilde{X}$ ...
0
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0answers
8 views
Coefficient of variation and residual standard deviation
From my knowledge, coefficient of variation and residual standard deviation are highly correlated. Such that if we find a significant change in one, we will find a significant change in the other. In ...
0
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0answers
14 views
Interpretation of regression coefficients: second-order differencing
Main Question: How are the coefficients of the second-order differenced explanatory variables to be interpreted? (See the attached screenshot of my result.)
Analysis framework:
I examine the ...
1
vote
2answers
25 views
Estimating effect of linear regression coefficients with multicollinearity
As I didn't find a satisfying for that questions I try it here:
I have a multivariate Lineare Regression model with some correlated predictor variables. The "simple" question I want to answer is: "If ...
0
votes
0answers
20 views
How to determine predictor importance at each level of an HLM model
I am working with a Hierarchical Linear Model (HLM). I want to determine which predictors are important at each level of the data. Across different hierarchical levels the fixed effects along with the ...
2
votes
2answers
40 views
Interpreting regression coefficients when the dependent variable is in percentages?
I have a dependent variable that is % of students graduating, but the explanatory variables are all absolute numbers, such as number of applicants and college fees. How would I interpret a coefficient ...
1
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0answers
38 views
Logistic Regression with categorical predictors - how to report?
Hello Stack Exchange.
I need to run a logistic regression to determine the significance of the effect of 5 categories of one variable on my dependent variable. I just can't find online anywhere how ...
1
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0answers
22 views
Calculating standard error of coefficients in segmented regression
I know this is kinda stupid question to ask here but just to make sure that I am doing this correctly, here it is anyway:
Consider the following equation resulted from segmented regression:
$$\hat ...
0
votes
0answers
17 views
Comparing independent MRDM models (multiple regression on distance matrices)
I am conducting Multiple Regressions on Distance Matrices (MRM or MRDM) to estimate the influence of 3 independent variables (IVs) on intraspecific $\beta$-diversity (my response variable DV) between ...
2
votes
1answer
47 views
REGRESSION :A log-linear interaction term
How do I interpret a log-linear interaction term, is it possible?
My model:
$Y= B_1 + B_2\log X_1 + B_3X_2 + B_4(\log X_1 X_2) + u $
2
votes
1answer
51 views
Interpreting coefficients and understanding logistic lasso
In lasso regression, increasing the regularisation strength/shrinkage penalty eventually forces all of the regression coefficients to zero. In this instance the regression is logistic.
The plot shows ...
2
votes
1answer
27 views
Does dummy code a variable affect the intercept in a linear regression model
My colleague and I were both using R to fit a linear regression with the same dataset and same variables. The outcome variable is test grade while the independent variables are gender, age, and times ...
0
votes
1answer
25 views
Interpretation of logistic regression coefficients when there are multiple levels
Suppose that the model had the following output:
...
0
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0answers
8 views
Interpretation of coefficients for DV in shares
I very ensure about following interpretations, hence I would be very thankful for any advice. Let's say that my dependent variable is a percentage of managers in total employment ((managers employed ...
0
votes
1answer
14 views
the constant coefficients are penalized in the ridge logit conditional model?
I am estimating a conditional ridge logit model, there is very little bibliography about it, and I do not know if the constant coefficients are penalized. My model has 2 variables and 3 alternatives, ...
3
votes
0answers
79 views
Decomposing R^2 into independent variables
Consider a linear regression model:
$$y = β_0 + β_1X_1 + β_2X_2 + ... + β_kX_k + ε$$
where $R^2 = 1 - (SSR/SST)$.
I would like to determine the contribution of a factor $i$ (call it $R^2_i$) into ...
0
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0answers
18 views
Correlation formula for a Quadratic
I have used quadratic regression on a dataset to find the graph of best fit, that is, finding the coefficients a, b and c in the general formula of y = ax^2 + bx + c.
Having done that I would now ...
6
votes
2answers
377 views
Invariance of results when scaling explanatory variables in logistic regression, is there a proof?
There is a standard result for linear regression that the regression coefficients are given by
$$\mathbf{\beta}=(\mathbf{X^T X})^{-1}\mathbf{X^T y}$$
or
$(\mathbf{X^T X})\mathbf{\beta}=\mathbf{X^T ...
0
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0answers
29 views
Regression coefficient signs different for log/asinh and level versions of same variable
I ran two regressions. First, say, y=βx, and the second one, asinh(y)=βx, which I read is asymptotically equivalent to log(y)=βx, where x and y are the same variables with same data set for these two ...
1
vote
1answer
38 views
How to account for incrementation in a log-linear model
I want to perform a mixed regression analysis with random intercept and uncorrelated random slope after multiple imputation.
The dependent variable is continuous, namely a duration as number of days ...
1
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0answers
29 views
Standarized coefficients of a general additive model GAM
I am using a GAM model to study the effects of time (in weeks) and quality parameters (qp1, qp2, qp3 and qp4) on a response variable. Since the effect of time is modelled best by a spline, I am using ...
5
votes
1answer
41 views
Pairwise comparisons of regression coefficients [duplicate]
I would like to know how to make quickly pairwise comparisons of regressions coefficients across three or more groups in R.
Here is a small example:
...
0
votes
1answer
25 views
Interpreting ridge coefficients as a function of regularization
Data consists of 40 observations with 4 dimensions and a response-variable.
When doing a ridge regression on my data and plotting the coefficients and coefficient errors (MSE of the ridge ...
0
votes
0answers
20 views
How to prove that conditional distribution for Y given OLS for simple linear regression do not depends on original parameters? [duplicate]
How to prove that for a simple linear regression model: $$y_i=\beta_0+\beta_1 x_i+\varepsilon_i,$$ the conditional distribution
$$Y|\hat{\beta}_0,\hat{\beta}_1$$
do not depends on $\beta_0$ and $\...
1
vote
0answers
25 views
Interpreting log coefficients in differences model (time series/panel)
I am struggling with the interpretation of coefficients in
$\delta(\log y)=\alpha+\beta\delta(\log x)$
Usually in a $y=\alpha+\beta x$ model, $\beta$ represents change in $y$ corresponding to unit ...
1
vote
0answers
23 views
Interpreting log transformations in a logistic regression
This stats.stackexchange post contains explanation of how to interpret transformed variables in linear regression.
In particular, I found this snippet in Graham Cookson's answer (2nd answer):
Y ...
