**3.239 multiple-regression questions.**

I believe the rule of thumb is at least 10-20 observations per predictor variable, but I was hoping to get some additional clarification.
Suppose a hypothetical example with dependent variable of ...

I want to use a Difference-in-Difference approach. In order to make sure treatment and control group are similar, I want to use a propensity score matching before the DiD approach. What I do is to ...

I have took a look in a video that the guy was doing a regression analysis for forecast sales.
He has a dataset with two columns (date and sales, for the past). He made a transformation on the ...

Hopefully somebody can help me or point me in the right direction!
I've done a study comparing the effect of a training on a continuous dependent variable, let's call it symptom severity.
The study ...

What is a suppressor variable in multiple regression and what might be the ways to display suppression effect visually (its mechanics or its evidence in results)? I'd like to invite everybody who has ...

I observed learners in study groups over a period of 3-10 study group sessions (students were free to decide how often they want to meet to learn within this range). For each session, each learner had ...

I have a D-W = 1.312 with a sample of 22 cases.
Is it a good value for running a multiple linear regression model?

This question is regarding the use of imputation methods, such as Multiple Imputation, for multiple regression models.
It is often suggested that one should compare the regression model created using ...

Please I am exploring for multicollinearity in my data between socio-economic characteristics. I ran a collinearity diagnostic test and I have a conditional index of 6.235 which is less than 10. I ...

I have trained a linear regression model, using a set of variables/features. And the model has a good performance. However, I have realized that there is no variable with a good correlation with the ...

I'm trying to solve a multiple linear regression problem. The main aim behind solving it is to find out how scipy.linalg.lstsq() solves it and finds out the required coefficients.
When researching it,...

Assume that the true (but unknown) relationship in a population between $Y$ and $X1, X2, X3, X4$ is $$Y=\beta_0 + \beta_1 X_1 + \beta_2 X_2 + \beta_3 X_3 + \beta_4 X_4.$$ Further assume that I have a ...

Methodological question in preparation of an experiment with 4 groups of 10 growth chambers each.
It is hypothesized that parasite infestation will affect growth chambers climate, as measured hourly ...

While researching OLS, I found out the equation to calculate coefficients as:
$$
\beta = (X^\top X)^{-1}X^\top y
$$
(Ref: https://en.wikipedia.org/wiki/Linear_least_squares)
However it does not ...

I was asked to do a correction of p-values for my analyses, but I'm not sure what p-values I am to correct, and presuming I'm using Bonferroni, what is the number that I am dividing the .05 level with....

I am studying the factors influencing the annual salary for employees at a undisclosed bank. The regression model that I have decided to employ is as follows:
\begin{equation}
Y_{k}=\beta_{1}+\beta_{...

If an existing questionnaire does not exist to tap into a construct, is it better to change the instructions of a preexisting measure that isn't quite tapping into the variable of interest to have ...

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 ...

I am dealing with a noisy dataset that has a certain amount of error for every estimator. Say, xi's are plus/minus a constant.
I am wondering if there is a way to handle these errors or at least see ...

Is there any literature, examples, advice, etc. out there on creating real-time detection algorithms from a multivariate longitudinal block-design experimental data? (same 5 variables being collected ...

I am preparing for a few prob/statistics exams, presently learning conditional probability,Bayes theorem etc
I wanted to learn the regression portion mentioned in these as soon as I can, since I may ...

I'm aware of the formula for univariate linear regression. Can you share any similar equation for regression with more than one independent variables?

When performing a general linear hypothesis test using the glht function within the R multcomp library.
For example:
...

Consider the linear regression model $$y_t = \beta_1+\beta_2x_{t1} + \beta_3x_t2 +u_t.$$
Rewrite this model so that the restriction $\beta_2 - \beta_3 = 1$ becomes a single zero restriction.
...

Consider 2 regression models on the same data set.
Model 1 : $R^2 = 90$% , $R^2(adjusted) = 80 $%, $R^2(pred) = 70$%
Model 2 : $R^2 = 60$% , $R^2(adjusted) = 59 $%, $R^2(pred) = 58$%
In the first ...

I'm currently working on building a predictive model for a binary outcome on a dataset with ~300 variables and 800 observations. I've read much on this site about the problems associated with stepwise ...

I want to run a time series regression over data is not spaced out in regular time intervals and where in some time periods there are multiple observations. Such in the picture below.
Is this ...

Consider the linear model estimated by OLS:
$$ y = X\hat{\beta} + \hat{u} = X_1 \hat{\beta}_1 + X_2 \hat{\beta}_2 + \hat{u} $$
We say that the above equation is the long regression,
Consider also ...

I am using OLS to estimate the effects of various factors on the sales of different items. The data are monthly, and vary somewhat in the number of monthly observations available (some of the items ...

tl;dr: linear model is better than ANN and decision tree in timeseries regression task, why is that?
I have a time series dataset of 151 observations each with 43 macroeconomic variables. Some of the ...

I am measuring the proportion of different types of bacteria killed by 4 different antibodies (simplified for illustration)
...

I have a theoretical economic model which is as follows,
$$ y = a + b_1x_1 + b_2x_2 + b_3x_3 + u $$
So theory says that there are $x_1$, $x_2$ and $x_3$ factors to estimate $y$.
Now I have the real ...

I'm trying to figure out the best way to account for linkage disequilibrium in a cox regression, and would really appreciate your advice. I'm testing the effect of a particular allele on overall ...

I have a set of data and I wish to construct a multivariate regression model for predicting. I saw that if the variables are multi-colinear the multivariate regression model will be bad. I don't know ...

I am running a multiple linear regression analysis, both my dependent and independent variables are positive. However, the generated surface from the reduced model I got after stepwise regression ...

I have polynomial equation as
𝑦=𝑤1.𝑥1+𝑤2.𝑥2+𝑤3𝑥12+𝑤4𝑥22
It is linear in new dimensional space R4 and non linear in original space R2.
please correct me.

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 ...

Can anyone tell me why the p-values for two stage least squares for manual lm vs ivreg way ...

Assume I have an equation with 1 endogenous variable, and many other exogenous variables. Also assume I have 2 valid instruments for the endogenous variable for IV estimation.
If I were to estimate ...

I have an independent variable X and dependent variable Y so want too check the impact of X on Y both variables are quantitative ( impact of X quantity on Y quantity ). Also X can be splitted to ...

I want to run a multinomial logit regression using the multinom() function from the nnet R package. I need some help me in the interpretation of different formulas. My dataset have 3 IV (age (3 levels)...

I would like to compare the affect of parameters x and z on dependent variable y.
I'm not sure how to know whether z or x is 'better'/'stronger'/'more likely to be a driver' of y.
For x, when I ...

In experiment I have measured the grow of one plant on 40 locations. At one location different number of plants were measured, but always the same species. The distribution of response variable is log-...

For simple linear regression (SLR), in order for $R^2$ (the coefficient of determination) to be a meaningful measure, it must be true that $X$ and $Y$ are linearly correlated. Specifically, $R^2=r^2$, ...

I have 66 indicators of leadership, and I want to check which ones contribute the most to leadership effectiveness. I have performed EFA, resulting 8 constructs from leadership indicators.
Should I ...

it's been a while since I've had to do any statistics and I need a little help determining which statistical model/test to use in R. My background is more with multivariate stats, so it's been a while ...

Suppose I construct the variable $U_i = S_i + T_i $, and I want to estimate the equation
$$ Y_i = \alpha + \beta U_i + \gamma X_i + \epsilon _i $$
Suppose $X_i$ and $S_i$ are exogenous, but $T_i$ is ...

Does anyone have a reference to an explicit formulation of multiple regression, but in which the bias term is taken out and treated separately? I would especially be interested if either ridge ...

It seems that multiple regression is a better way to do analysis. For example,the ANOVA simply gives t-value (or F-value for two or more variables) and does not indicate magnitude of effect. Contrary-...

How should I perform a general linear hypothesis test in R on the coefficients of a fitted model that are represented by treatment contrasts? In particular with regard to the differences between the ...

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