Regression that includes two or more non-constant independent variables.

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Can I have an IV which does not have main effect on DV directly but might have an interaction effect with another IV on DV?

I am inducing envy (IV 1) to see the effect on focusing illusion/anchoring bias (DV). Since I am going to induce envy by showing attractive others' pictures,then gender will play a role because ...
3
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1answer
24 views

Interpret Regression Coefficients After various Differencing

There are few explanations I can find that describe how to interpret linear regression coefficients after differencing a time series (to eliminate a unit root). Is it just so simple that there is no ...
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31 views

Spurious regression /correlation

In a time series regression I am finding a certain predictor variable significant which should not be, according to the client. Could this be due to the higher variance that this predictor exhibits ...
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18 views

How to assess variable to transform in multiple regression?

I have a multiple regression model and when I check its residuals vs fitted I have determined a transformation of some kind needs to take place ... but I don't know which variable to start with (4 ...
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9 views

How do I orthogonalize one variable to others in an ARIMA regression context?

I have one socioeconomic variable Y, with which I can correlate with variables V1, V2, V3, V4. So Y consists {Y1, Y2, ..., Yt}, V1 consists of V1_1, V1_2, ..., V1_t, etc. I put them into a seasonal ...
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11 views

Why is discrete cosine preferred to FFT in neuroimaging GLM

High-pass filtering is often used in neuroimaging data analysis. Commonly, whenever a general linear model is fitted to the data (as for instance in statistic parametric mapping) a number of columns ...
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16 views

k-fold cross validation for LASSO regression model

Assume we have a simple linear regression model expressed as $Y= X \beta + e$. We know that finding the regression coefficients $\beta$ using the LASSO method is performed by penalizing the Least ...
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16 views

Applying parametric tests on non-parametric data

I'm doing a research and I have some concerns, and I'd appreciate your kind assistance on them. Basically, I'm designing an instrument to measure something (a single dependent variable), and I'm ...
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1answer
17 views

Describing the target audience for a set of movies

I have several observations with both categorical and numerical variables relating to the personal details of surveyed individuals (such as age, gender, education and region inside the country they ...
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47 views

How to interpret a VIF of 4?

I am doing a multiple regression, trying to test the extent to which personal income changes and Presidential popularity can predict election results. I have a small sample size, unfortunately, as ...
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36 views

Why would I need both a validation set & a test set if I'm not selecting a model?

I have a dataset with two features and one outcome. I was asked to separate the data into three parts such that 70% of the data is a training set, 20% is for validation and 10% for testing. The model ...
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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 ...
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Improving estimates of linear system regression when parameters are unevenly weighted

I have a system with a linear model $ax + by = c$. I can adjust $a,b$, measure $c$ (with some error in the measurement) and then use linear regression to estimate $x,y$. The problem I'm running into ...
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+50

Can it be as accurate to model child-variables to estimate a parent-variable instead of modeling the parent-variable directly?

With time series data, let's say you want to model the return of the S&P 500. Could you get as good or better results by modeling each stock, and aggregating them to estimate the return of the ...
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1answer
49 views

How to start with regression analysis? 10 variables; 1M samples

My statistics knowledge is limited, and it appears that I have a task which would benefit from regression analysis. Please direct me. I've around 10 variables (A, B, C, ...) which might be related to ...
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How to analyze categorical dependent variable which can have multiple values for each participant?

I have a data set where people are asked to choose 0 or more options from a set of available options. About 2/3 of the sample select none of the options; most of the remaining participants choose one ...
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2answers
74 views

$R^2$ increases when removing predictors

I have a multiple regression model with many predictors (admittedly more than I want: 21). When I remove one of the predictors (leaving me with 20) my R squared increases a bit. Should this happen? Is ...
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12 views

How to quantitatively evaluate the impacts of each variables on the measured data

I am trying to evaluate the individual effects of A,B,C,D on Result. A and B are numerical variable and C, d are categorial. Could anyone give me some suggestions about what statistical method to ...
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27 views

Predicting categorical dependent with multiple categorical variables

I have a data set in which i have multiple descriptive columns. Things like annual income (which have been bucketed into 100k groups, years of experience, and age) as well as a string that indicates ...
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13 views

Multiple regression using data with mixed categorical and continuous variables

I'm new in statistics and machine learning. I have a problem to predict the price of the car. In my dataset there are 3 continuous variables and 5 categorical. Continuous variables: mileage, engine ...
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10 views

Multiple Regression: 3 groups for IV, post-hoc equivalent?

I would like to test the following: DV - Brain volume IV - Participant Group (Patient with Mild Symptoms, Patient with Severe Symptoms, Controls) Covariates - Age, Gender, IQ I wish to use ...
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1answer
28 views

Are R-squared and F the same for variables in Multiple Regression in R

I ran a multiple regression analysis and got significant results for lFreq, Len variables, and interaction lFreq x Len. Now I need to report these results and I am a bit confused whether F(7, 924) = ...
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40 views

P-Values decrease when additional significant variables added (multicollinearity?)

I am doing a study for my masters correlating two separate development indicators to election results for the incumbent government. Unfortunately, I was only only able to get 11 years worth of data ...
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31 views

Arbitrary prediction interval with random independent variables

I have a equation with the parameters determined from multiple linear regression: $$ Y = \beta_0 + X_1 \beta_1 + X_2\beta_2 $$ I would like to forecast the distribution of $Y$ numerically, in other ...
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16 views

Multiple Regression for Biased Sample

I have a sample in which most of the variables have zeroes as their value.99 percentile of each variable holds some value.which method/approach should I apply for such a biased sample.
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Interpreting linearity in regression when there are outliers

I am trying to determine whether this regression meets all of the assumptions one needs to adhere to when carrying out a multiple linear regression. In looking at the residual plots below, it seems to ...
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27 views

How can I predict one time series using another time series?

Necessary Information: I have time series $X_t$ and $Y_t$ and $Z_t$, $t=0,...,N$. I want to develop a model to use $X_t$ to predict $Y_t$ where I know there exists a relationship $Y_t = Y_{t-1} + Z_t ...
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41 views

Why is multiple regression to be preferred over simple linear regression? [closed]

How does a multiple regression differ from a simple linear regression and why is the use of a multiple regression generally preferred over a simple linear regression?
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14 views

Regression coefficients in terms of means, st.devs and correlations [duplicate]

I am dealing with bivariate regression. Can somebody post formulas for the betas in terms of means, covariances, correlations, etc. i.e. summary statistics rather than the actual, full data set?
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16 views

Data transformed in order to satisfy regression assumptions but no effect

I am trying to use "Cursor" , "PostCursor" and "CTLE" to predict "left", and I added interactions and quandratic in the model. ...
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20 views

The best model to analyse this data set: Comparing bacteria communities within calves

The design is like this: I have 18 calves in the experiment, and all these calves were divided into 3 groups with 6 calves in each group. The 6 calves in group 1 were euthanized at the end of the ...
2
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1answer
12 views

mediation hypotheses

I am examining a loyalty program's (LP) effectiveness on customer loyalty across members and non-members. I first hypothesised members will perceive higher levels of switching costs (SC), and exhibit ...
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35 views

Help regarding multiple regression with repeated independent variable measurements

I've spent a fair amount of time looking at previous posts related to my question. However, I've been unable to find a discussion that fully captures the difficulties I'm having - either because it ...
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38 views

Interpreting cubed root transformation

I’m running a linear regression where my response variable is mean satisfaction score of GP practices, while one of the predictor variables is funding received. I used a cube root transformation for ...
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13 views

performing multivariate binary regression when the independent variables are subset to other

say i have a data of cancer patients who have fever and i want to see what factors are associated with mortality. After performing univariate analysis (crosstab in SPSS), i have 3 factors with p-value ...
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2answers
69 views

regression analysis with confounding variables, how to interpret your main coefficient when controlling for confounders

I'm interested in the effect of X on Y and want to adjust for confounding variables in my regression model. If the model (regression, F-test) is not significant but the predictor of which I'm ...
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30 views

Linear regression with parameters, for weather normalization of utility bills

I have a problem in "weather normalization of utility bills" : I would like to find $X$ such as $AX = Y$ where $Y$ is the vector of the monthly Consumption of electricity per day, and $A$ is a matrix ...
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25 views

Calculating Absolute Principal Component Scores from varimax-rotated principal components scores

In many receptor- modelling studies, after performing the PCA analysis, they often "rescale" their varimax-rotated PC scores (which are standardized with mean zero and standard deviaiton of 1) to ...
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Creating relationships between dependent variables

I have data on a $M$ systems (say different material alloys). Each system (material) has $N$ variables (properties). I would like to correlate one variable(say material strength) of the system with a ...
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44 views

How can I calculate the variance of interaction term from an equivalent model without interaction?

Lets say that you have access to a model that estimates the mean of four independent groups like m2 below, but these groups have been formed from two factors (a & b) and you want to instead ...
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68 views

Can I use logistic regression if the distribution of proportions is skewed & lies in the middle of the [0,1] interval?

I am conducting a logistic regression in order to predict the service point win percentage of a tennis player. In terms of data - I have (for each player A) approx 300 matches - for each match I have ...
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75 views

How to use multiple regression when I have several levels for categorical variables? How do I code for this?

My data is from a cross sectional study looking at pathogen status among 300 patients along with other clinical parameters. There is no control group. I am using Stata. (edit: This is a ...
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How to use multilevel analysis (MLM) in SPSS when I have 1 DV (frequency of absenteeism) and multiple IVs (more then ten) over three levels?

My aim is to analyze data in SPSS from an employee survey (approx 2000 subjects) and link this data to absenteeism. I think I should use multilevel analysis, but I am not experienced with MLM. DV = ...
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80 views

How does one perform multiple non-linear regression?

I performed an experiment where I took the heights of plants and measured a number of environmental conditions (air temp, soil temp, lux, air humidity, soil pH, wind) for each of those plants. I want ...
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1answer
24 views

Response Surfaces and Multiple Linear Regression

Suppose I have a MLR equation $y=b_0+b_1x_1+b_2x_2 + e$. If I were to plot this equation, should it not produce a "line" ? I have looked into response surfaces and I am not sure how one would derive ...
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2answers
35 views

Combining Linear Regression and Time Series

I’m trying to figure out if I can combine linear regression and a time series model to help make predictions about the number of shots in a soccer game. When I perform the linear regression, I have ...
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A Regression to predict tennis player's service point win percentage - Which of these two models makes more sense?

I am conducting a regression in order to predict a tennis player's service point win % i.e. the percentage of points he wins when he is the server. Model 1 If my DV data lies in the range 0.3-0.9, ...
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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 ...
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42 views

Forecast multiple regression in R

I created for the following data set a multiple regression. Now I would like to forecast the next 20 data points. ...
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35 views

Could we use multiple regression if the data do not shown the linearity?

I have a problem with my research, actually i want to use multiple regression to analyze my research, but i have problem. 1. Assumptions not fulfilled (normality and nonhomogeneous) 2. The plots ...