The parameters of a regression model.

learn more… | top users | synonyms

1
vote
0answers
25 views

Simple linear regression using aggregated data

I have an old exam paper with a question on simple linear regression. It outlines the following scenario: A researcher collects data on 200 people, 20 in each of 10 regions. He then calculates ...
3
votes
0answers
39 views

What explains the correlation between the slope and intercept?

If $R^2$ explains the variation explained by a model, what explains the correlation between the coefficients given for a slope parameter and an intercept? I have been thinking of it in two ways: If ...
0
votes
0answers
20 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
21 views

Partial Least Squares regression

Assume we have a simple linear regression model expressed as $Y= X \beta + e$, where $Y$ is a vector of size $n \times 1$, $X$ is a matrix of size $ n \times p$, $\beta$ is the regression coefficients ...
1
vote
0answers
6 views

Changing polynomial degrees leads to different coefficients in Fuzzy RDD

I am running a Fuzzy RDD and I am getting some unusual results, the coefficient of interest changes sign and significance with different polynomial specifications. When using a linear polynomial ...
0
votes
1answer
20 views

categorial variables in LASSO regression

i just built a logistic regression model via Lasso Penalization. Now i'm trying to interpret the coefficients. One is "days". I have a coefficient for "days". when i do a normal logistic regression ...
0
votes
0answers
22 views

What happens to the coefficients when we switch labels (0/1) - in practice? [migrated]

I am trying to see in practice what was explained here what happens to the coefficients once labels are switched but I am not getting what is expected. Here is my attempt: I am using the example of ...
0
votes
0answers
22 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
0answers
5 views

Coefficients for regression in levels from Estimated First Difference Coefficients

I would like to know if there a simple way to compute coefficients for a regression in levels after having estimated a regression in first differences. Having estimated yt - yt-1 = a + b(xt-xt-1) ...
1
vote
1answer
108 views

What exactly is the critique in this regression?

Warning: I might be forgetting basic statistics here. Please edit title if it can be improved. This paper, seemingly summarized in the fancy ZUI slideshow here, points out a possible "critique" in ...
2
votes
0answers
16 views

Can I interpret Standardized Regression Coefficients for an Interaction Term?

can I interpret standardized regression coefficients for an interaction term that is based on a binary and continuous variable? How would I interpret it: Would I add the standardized coefficients if ...
2
votes
1answer
43 views

Regression coefficients tests before or after model selection

I have a set of data containing 4 predictors (environmental conditions and animal size) and one predicted variable (animal growth rate). I want to fit a regression model to this data. I have two ...
2
votes
1answer
60 views

Why beta sign is different than correlation sign? [duplicate]

I am trying to interpret the sign of my 5 x-variables against y-variable. The sign of some coefficients in the regression output (command: reg) are different than the signs under correlation matrix ...
0
votes
0answers
9 views

GLHT with GLM negative coefficients?

I'm trying to do a glht with this glm, but I'm getting some weird results. My glm is ...
5
votes
1answer
141 views

Regression slope that increases persistently as my sample size increases

I found a peculiar feature in some data that I am analyzing and was wondering whether there was a technical term for this type of phenomenon and whether anyone has come across it before. I am doing a ...
0
votes
1answer
35 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 ...
3
votes
1answer
76 views

How to interpret meaning of regressors in this logistic regression model?

I'm trying to understand the model in this paper where they treat the item response theory model as a form of logistic regression. In the model the probability of getting an item (question) correct ...
0
votes
0answers
36 views

How to interpret economic significance if variable is zero most of the time

in my paper I constructed a continious variable which measures the strength of a certain event. If there is no event the variable is zero. So my panel looks like this: ...
0
votes
0answers
18 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 ...
1
vote
1answer
27 views

P-values for regression coefficients in total least squares regression

I want to calculate the p-value for the beta estimated in Total (orthogonal) least squares regression. Do I need to calculate the standard error of the estimates in ...
0
votes
0answers
15 views

Replicating a paired t-test via regression

Setup: I have a survey where subjects had to divide 600 points between two investment opportunities (option A and option B). Thus, I always have invest_A = 600 - invest_B. Goal: Check whether ...
0
votes
1answer
24 views

Multinomial regression interpretation SPSS [duplicate]

-- start reading from the edited part -- When running a multinomial regression the two values we are really interested in are the values 'B' and B(Exp)'. Let's say we have (fictive numbers): B: ...
0
votes
0answers
32 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
23 views

Does the coefficient of a feature play a role in picking variables for linear regression?

In general, when we do a linear regression, we keep only those variables that have p-values below 0.05 or 0.01. While eliminating those variables whose p-values are above our thresholds, do the ...
1
vote
1answer
23 views

How are the results of multivariable quantile regression interpreted?

Is multivariable quantile regression interpreted the same way as a multivariable linear regression would be interpreted? For example, would I say something like "the coefficient represents the ...
0
votes
1answer
13 views

Time dummy variable coefficient

What to do when time dummy coefficient turns out to be statistical insignificant? Can it be justified somehow? I have a case when time dummy coefficients are insignificant (p values > 0.1).
1
vote
1answer
22 views

Relationship: Regression Coeffecient and Line Plot Trendline Slope

Why does the slope of my line fit plot not match the coefficient of the same variable in my regression? For one of the variables, the coefficient is positive while the line fit plots trendline is ...
1
vote
1answer
17 views

How do you read the coefficients in Structural Equation Model for prediction?

I understand that in regression, the beta weight can be used for prediction. For example: Depression =~ 1 + 0.5*Loneliness Suppose that depression and loneliness are measured with Likert Scale from 1 ...
1
vote
0answers
37 views

Inconstant logistic regression coefficients each time algorithm is run [SOLVED] [closed]

I'm running a logistic regression to find a relationship between falls and drugs taken by someone. What happens is that every time I re-run the algorithm it gives a different result. The table is ...
1
vote
0answers
13 views

Coefficient in linear regression changes drastically if additional variables are added. Why? [duplicate]

n <- 100 x2 <- 1 : n x1 <- .01 * x2 + runif(n, -.1, .1) y = -x1 + x2 + rnorm(n, sd = .01) summary(lm(y ~ x1))$coef Coefficients (all significant): ...
0
votes
0answers
16 views

Is there a way to do logistic regression model selection of up to 5 variables each from a pool of ~70 variables

I'm trying to determine the best logistic regression model to estimate the probability of 0 in streamflow rates. My response for the glm object is one vector of the sum of all the days the recorded ...
1
vote
1answer
38 views

interpretation of coefficients from linear regressions with log dependent variable

I have a seemingly trivial yet troublesome question. Let's consider the following model: $$\ln(y_i)=\alpha + \beta D_i + \epsilon_i$$ where $D_i$ is a binary variable that indicates whether ...
0
votes
0answers
14 views

Taking differences, indexes or levels in regression analysis?

I am new to econometrics and regression analysis and I am trying to make a decision on which path to follow on my regression. I have cross sectional data, and I want to estimate the impact of ...
0
votes
0answers
39 views

What does the P value in restricted cubic spline plot mean? [duplicate]

What does the P value in the following example mean? ...
1
vote
0answers
29 views

Seperate regressions approach vs. interaction term approach

I am writing my thesis in finance, and my thesis advisor want me to do a categorical analysis, where I include control variables. He tells me I cannot simply include interaction terms (i.e. category x ...
0
votes
0answers
53 views

Interpreting Regressions with (growth) rates as dependent variable

I have several regressions and I care about the interpretation of the coefficient(s) (as marginal effects or very small changes). Y is a variable which is a ratio, e.g. a growth rate or a share (not ...
0
votes
0answers
76 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
1answer
30 views

There are low variations in the explanatory variables

I am running a regression and find coefficients of my explanatory variables very interesting (they are dummy variables). When I informed that to my lecturer, he told me that there are not much ...
0
votes
0answers
16 views

Which test-statistics do I use if I just want to test one particular regression coefficient

Hello my Question is this. I want to test a model which has the form: $Y_{i,j}= \beta_0+\beta_1 I_{treatment}+ \beta_2j+\beta_3j*I_{treatment},$ (1) where $i$ is the Identifikation Number and $j$ is ...
0
votes
0answers
12 views

Comparing a regression in two scenarios

I am looking for some answers regarding regression. I am running a regression in scenario 1 and then same construct measured for a scenario 2, the scenario is different but the constructs are the ...
0
votes
1answer
30 views

How to deal with linear regression intercepts with high p-values in dichotomic classifier?

I have used a simple multivariable logistic regression (as you would get by default glm() with logit in R) in a problem of dichotomic classifier with approx. 100 predictors, i.e. quite a lot of ...
1
vote
1answer
38 views

How do I interpret interaction effects in a log-log regression model?

I have the following model: $\log(y)=\beta_0 + \beta_1 x_1 + \beta_2 \log(x_2) + \beta_3 x_1 \log(x_2) $ In interpreting the % change of $y$ that corresponds with a 1% increase in $x_2$ at a ...
2
votes
1answer
23 views

Backtransform coefficients of a Gamma-log GLMM

I am analysing data from an exclosure experiment, this means for several years, goats were kept outside a fence and inside the fence, plants could grow without being grazed. Outside the fence, grazing ...
0
votes
1answer
12 views

Clarification on Prediction with a Regression Model using Centered Variables

As I understand it, for a regression model, centering the variables around their means can be helpful since it makes the intercept term the expected value of $Y_i$ when the predictor variables are set ...
0
votes
0answers
13 views

Variable contribution in Poisson regression

I am trying to quantify a contribution of X on Y. Imagine I have a time series (per day) of the next variables: Y, X1, X2 Using a scatter plot on visits vs. each variable I have tested that the ...
1
vote
2answers
45 views

Finding best model for small volume data

I know, this topic was mentioned many time at this forum. However I failed to find any detailed suggestions. I am currently involved in the analysis of medical data. The way I usually did this in ...
0
votes
0answers
18 views

Comparing Cox models

We want to compare different methods of modelling a continuous covariate (X) in a Cox model. For example, in the first model we use X in its continuous form. In a second model we categorize X into ...
0
votes
2answers
50 views

Survival regression variance estimates

I would like help understanding why a survival regression with no censored data-points does not give the same variance estimates as a linear model (see code below). I think it must be something to do ...
1
vote
0answers
21 views

Hierarchical Bayesian Regression with an Indicator Variable, one group has all zeros for the IV Variable

I'm attempting to form a Bayesian Hierarchical Regression Model and one of my regressors is for an indicator variable. My hierarchy structure has separate group-level regressors related across-groups ...
2
votes
2answers
125 views

Is there something called “mean coding” (like dummy coding & effect coding) in regression models?

When we perform a regression analysis with categorical predictors, we can use (1, 0), called "dummy coding". The coefficients in this case represent the deviation of the groups' means from the mean of ...