# multiple-regression's questions - Chinese 1answer

3.239 multiple-regression questions.

### Multiple Regression - Minimum Observations Per Dummy Variable

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 ...

### Difference-in-Difference with multiple regression vs. matching combined with Difference in Difference

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 ...

### Using regression analysis for forecast - dummy encoding

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 ...

### Interactions in regression with two categorical variables

0 answers, 7 views multiple-regression interaction
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 ...

### 35 Suppression effect in regression: definition and visual explanation/depiction

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 ...

### HLM using lmer in R

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 ...

### what is a good value for Durbin-Watson test in regression models?

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?

### Imputation and Multiple Linear Regression

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 ...

### 1 Multicollinearity in BLR

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 ...

### 16 How is it possible to obtain a good linear regression model when there is no substantial correlation between the output and the predictors?

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 ...

### SVD vs scipy.linalg.lstsq() [on hold]

0 answers, 30 views multiple-regression svd scipy
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,...

### 5 Does more variables mean tighter confidence intervals?

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 ...

### Linear mixed model methodological questions for time series sensor and non sensor data

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 ...

### Calculation of intercept in multiple linear regression (OLS)

1 answers, 25 views multiple-regression least-squares
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 ...

### 1 Correction of p-values for multiple regression models with multiple comparisons

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....

### 4 Feasible Generalized Least Square in R

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: Y_{k}=\beta_{1}+\beta_{...

### Multiple Regression study design - questionnaires

1 answers, 402 views multiple-regression survey
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 ...

### 2 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 ...

### 1 How can we address the error associated with estimators in linear regression?

0 answers, 12 views regression multiple-regression
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 ...

### How to build real-time detection algorithm from a time-series block design experimental design?

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 ...

### prerequisites to learn linear and polynomial regression [closed]

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 ...

### -1 What is the equation/formula for coefficients of independent variables in multivariate linear regression? [duplicate]

0 answers, 15 views regression multiple-regression
I'm aware of the formula for univariate linear regression. Can you share any similar equation for regression with more than one independent variables?

### Which 'single-step' multiple comparison test is being employed within R multcomp::glht?

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

### constructing the unrestricted model

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. ...

### Which linear regression model is better? [closed]

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 ...

### 10 Interpretation of LASSO regression coefficients

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 ...

### Time series or panel data models that can deal with irregular time intervals and multiple observations in some but not all time periods

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 ...

### 1 What is the relationship of long and short regression when we have an intercept?

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 ...

### 1 Should I pick a constant sample size for regressions on data with different available n?

0 answers, 76 views multiple-regression sample-size
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 ...

### 2 Why is my machine learning algorithms i use worse than standard multivariate linear regression?

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 ...

### comparison of multiple groups when the dependent variable is a percentage

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

### 13 Estimating $b_1 x_1+b_2 x_2$ instead of $b_1 x_1+b_2 x_2+b_3x_3$

3 answers, 1.806 views regression multiple-regression endogeneity
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 ...

### 1 Cox Regression and Linkage Disequilibrium

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 ...

### 2 What is the difference between multicollinearity and correlation?

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 ...

### Negative values in Multilinear regression model?

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 ...

### -1 is polynomial regression linear in original space? [duplicate]

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.

### 3 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 ...

### 1 How come p-value for ivreg and manual lm differs so much?

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

### 1 OLS vs IV estimates - Sign and Significance

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 ...

### 1 What regression analysis technique to use?

1 answers, 33 views regression multiple-regression
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 ...

### Interpretation of multinom's formula in R

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)...

### 1 Interpreting and comparing linear and quadratic regression

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 ...

### 1 GRM or mixed effect models

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-...

### 2 $R^2$ (coefficient of determination) and linearity in multiple linear regression

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, $R^2=r^2$, ...

### 1 Should I perform CFA after the EFA or can I move directly to multiple regression analysis?

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 ...

### 1 Which statistical test to use in R? Unbalanced design with one dependent variable and multiple independent variables

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 ...

### IV regression: endogenous variable is sum of exogenous and endogenous

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 ...

### Formulation for multiple regression, but with the bias term taken out and treated separately [duplicate]

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 ...

### 1 What are the limitations of ANOVA vis a vis multiple regression analysis [duplicate]

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 to perform general linear hypothesis test on fitted model with treatment contrasts in R?

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 ...