Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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39 views

How to standardize the variables in R for regression analysis

I have been looking at some tutorials and articles and couldn't get a scenario where two variables are in different scales and used in modeling. So, firstly lets assume I have one metric of numeric ...
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0answers
14 views

Comparing means of different training programs in R

I have a data set with performance and training data that looks something like (this is not the exact data, but gives a general idea): ...
2
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1answer
17 views

Testing linear restriction of parameters of ordered logistic regression models

Given the ordered logistic regression model: $outcome=\beta_0+\beta_1X_1+\beta_2X_2+\beta_3X_1*X_2$ Can I test linear restrictions on the parameters? For example I would like to test $H_0: ...
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0answers
6 views

stacked polynomial regression vs polynomial in the Xi

The Ramsey RESET (Regression Equation Specification Error Test) can tell if the model is under specified. The test can suggest that polynomial regression may be in order. ...
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0answers
19 views

How to cross check all the steps in a Machine Learning Task? [on hold]

I am an arts student learning aspects of Machine learning. I am sort of a self learner. My teachers and peers are generally happy the way I work out problems. But sometimes I forget any of the key ...
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0answers
9 views

No beta weights for a group in logistic regression

I am running a multinomial logistic regression with the multinom function in R, nnet package. I have four response categories (1, 2, 3, 4) that correspond to results from a clustering approach over 2 ...
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0answers
17 views

L1-based feature selection, then classification

Does it make sense to use L1-based feature selection to reduce the feature set of a model, then use another L1-based machine learning algorithm to train the model on the selected set of features? For ...
0
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1answer
38 views

Selecting the best GLM (generalized linear model)

GLM (family=binomial) is foucusd on when the response is dichotomous(yes/no, male/female, etc..). I'm wondering how to judge if the model we built is good eough? As we know, in OLS regression some ...
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0answers
10 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 ...
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0answers
7 views

MLR, should all interactions be included even when irrelevant for tested hypothesis?

I have two simple questions yet I could not find a direct answer to either of them, so I would be thankful to anyone who could help me. I have 3 independent variables, X, Z and Q, where X is ...
0
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1answer
14 views

Coding factors with non-numeric settings

For my role as a TA I am assisting the instructor in developing curriculum based on DOE and statistics. We have a set of failure strengths (the output/dependent variable) for several glass rods. The ...
0
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1answer
21 views

Multivariate Regression Analysis in SPSS

I am using SPSS to perform a multivariate regression analysis. I have 4 factors, Group (1,2), AgeGroup (1,2), Sex (0,1), and handedness (0.1) with 4 dependent variables. My question relates to ...
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0answers
12 views

Encode special values in continous predictors

I have continuous variable with missing values. Missing values are of different types (indicated by special values such as 991, 992). How do I best encode my data for logistic regression? I can create ...
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1answer
20 views

Natural Resource Management: How do I estimate the odds ratio and confidence intervals from model-averaged estimates?

I'm currently working on a model selection analysis in the field of natural resource management. My research question is: what variables are important to an avian species nest site selection. My ...
0
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0answers
12 views

How to specify a multi-instrument 2SLS [migrated]

I'm looking for a compact way to specify a multi-instrument 2SLS in R. Imagine that there are four treatment categories (A, B, C, and D). There are two waves of measurement, Y_1 and Y_2. A ...
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0answers
14 views

Modeling rent share as a function of income [on hold]

I want to model the share of income spent on rent as a function of income and a few other variables. Now the dependent and explanatory variables are not dependent. Is this a problem.? Or is it ...
3
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3answers
210 views

Interesting Logistic Regression Idea - Problem: Data not currently in 0/1 form. Any solutions?

I am attempting to conduct a logistic regression for a tennis analytics project, endeavoring to predict the probability of a player winning a point in which he is the server. My response variable ...
0
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0answers
13 views

Logistic regression: Include a specific time variable to account for unexplained changes over time?

I am measuring the effect of specific marketing activities on the likelihood to buy a product. The Marketing activities start on a specifc date. All the products sold before this date a marked with a ...
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0answers
16 views

Removing outliers based on cook's distance in R Language

I have this R code for linear regression: fit <- lm(target ~ age+sales+income, data = new) How to identify influential observations based upon cook's distance ...
2
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0answers
21 views

Fixed Effects vs Lagged DV vs. First Differences Regression

What are the differences between using unit fixed effects, unit fixed effects and time fixed effects, lagged DV, or first differences to analyze a time series with 4-5 time periods and 35-50 units per ...
6
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3answers
97 views

Can Random Forest be used for Feature Selection in Multiple Linear Regression?

Since RF can handle non-linearity but can't provide coefficients, would it be wise to use Random Forest to gather the most important Features and then plug those features into a Multiple Linear ...
2
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0answers
12 views

Linear regression with prior on $\arctan \beta_1$

Suppose we have $\hat{y} = \beta_1 x + \beta_0$ (I ask only for the univariate case.) A typical Bayesian approach might involve Normal priors on both parameters. I was thinking today about a ...
0
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1answer
6 views

class is intervalar 0- 20 regression or NN?

The class is quantity of children. So at first I thought of a linear regression, but then, since it will never predict extreme values, but there will be lot's of zeros. Is there any problem of using a ...
1
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1answer
41 views

Find a best fit curve for a function f(x) = g(x+1)/g(x)-g(x+1)

I have a set of noisy data that can be described by a functional form. For each observation f(x), where x is an index that runs from 0-100, I know that f(x)=g(x+1)/g(x)-g(x+1). I would like to find a ...
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0answers
16 views

Correlation between different types of variables

I am running a logistic regression on a data set containing Continuous, Ordinal, Categorical and Dichotomic variables. I would like to know how to calculate the correlation for all possible ...
0
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1answer
35 views

Logistic regression is appropriate? Forecasting player’s serve point win % as a binary variable, w/ both numeric and categorical independent variables

I effectively want to model the probability of a player winning his service point (a point in which he is the server) based on the values of explanatory variables (namely court surface and opponent ...
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1answer
23 views

why in logistic regression the probability mass equal the count

It's said that logistic regression is well calibrated and preserves marginal probability. What does that mean? Thanks.
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14answers
2k views

Why would parametric statistics ever be preferred over nonparametric?

This may be a stupid question but it's been bugging me for years. Can someone explain to me why would anyone choose a parametric over a nonparametric statistical method for hypothesis testing or ...
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0answers
10 views

coding for multinomial logistic regression dv

I have run a multinomial logistic regression. One of the 3 IVs is categorical and has 5 levels and the one DV is categorical and has 6 levels. I coded the levels from 1-5 for the IV and 1-6 for the ...
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0answers
7 views

Linear Regression vs Single Layer Perceptron [duplicate]

What is the difference between a linear regression and a single layer perceptron, as their mathematical expressions are the same?
0
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0answers
24 views

Running repeated cross-validation for multiple models using same dataset (caret package)

I'm currently using the train() function in the caret package to run 10-fold repeated cv on a random forest model. I would also like to explore other statistical and machine learning models for use ...
0
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0answers
15 views

Exp(b) in multivariate Cox regression

I am trying to interpret the results of a Cox regression. I ran a multiple Cox regression analysis of an categorical variable—heart rate including 5 levels. I added covariates that were also ...
2
votes
1answer
34 views

When there is only one dependent variable, is partial least squares regression the same as principal component regression?

When there is only one response (dependent) variable, what is the advantage of partial least squares (PLS) regression over principal component regression (PCR)? My understanding is that PLS is only ...
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0answers
27 views

Analytic (inverse sampling variance) weight in stata

I have a question about using aweight in regression in Stata. I have school level data (mostly percentages) but I want also to take school size into consideration. ...
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0answers
7 views

Interpretation of standardized beta coefficient estimates and use within the exponential formula for prediction purposes

I'm working on a data set where I plan to use logistic regression to evaluate non-random habitat selection for a wildlife species. My dependent variable is 1 = used location by an animal and 0 = ...
0
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1answer
42 views

Linear regression with sine/cosine elements

How can you derive formula and regression coefficients for a regression model of a form $y(x)= A + B\, x + C\, \cos (2 \pi x) + D\, \sin (2 \pi x)$? I know that there are automatic tools who can do ...
-1
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1answer
35 views

Logistic Regression modeling in R

Consider this model: $Y_i$ ~ Bernoulli($\pi_i$) $X_i$ = 0,1 logit($\pi_i$) = $\lambda^{X_i}$ * $\beta_0$ This model simplifies to logit($\pi_i$) = $\beta_0$ , when $x_i=0$ , and logit($\pi_i$) = ...
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0answers
3 views

Does the cvglm function in boot package have arguments for mean centering and normalizing?

Does the cvglm function in boot package have arguments for mean centering and normalizing? If not, how can I run k-fold cross validation with mean centering and normalizing in R ?(especially for ...
0
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1answer
22 views

Whether to apply the logit transformation to proportional predictor variables in a multiple linear regression? [including proportions of 0.0%]

In a linear regression, I have a number of predictors variables that are expressed as proportions. The outcome variable is continuous. My residuals are not normally distributed, with a mild to ...
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0answers
13 views

Visualizing multi-class ROC analysis [duplicate]

I am running a multinomial logistic regression model (with 3 possible outcomes) in R. I am trying to find the best way to assess the predictive power/accuracy of the model, and the best thing I've ...
1
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0answers
23 views

Root-Mean Squared Error for Bayesian Regression Models

I'm trying to get a sense of my prediction errors for a Bayesian regression model and I was using the Root-Mean-Squared Error. My question is, since are predictions are stochastic, would it make ...
1
vote
1answer
31 views

How does one treat censored data in SAS?

I have some censored data and I'm not sure how to deal with it in my regression analysis. The study was not a time series and all examples I've seen in SAS have been in the context of survival ...
0
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0answers
11 views

Estimating a gravity Modell Stata [on hold]

I am trying to estimate a gravity modell for trade analysis. My dataset contains 219,573 observations from 1948-1997. I tried xtset to get an overview about how balanced the panel actually is.. My ...
0
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1answer
45 views

regression with ratio variables

I plan do run a regression analysis with ratio defined variables such as (FX loans/ total loans, tangible assets/total assets etc.) and I have only 13 annual observations. This regression is needed to ...
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0answers
56 views

What is the difference between Fisher's regression and Durbin & Watson's suggested regression? [on hold]

What is the difference between Fisher's regression and Durbin & Watson's regression? Durbin & Watson suggested the error terms are unobserved. Is this important? "Testing for Serial ...
1
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1answer
28 views

Online linear regression. Possible or not? [duplicate]

I don't have a strong background in statistics, but I'm a programmer and needed to implement some statistical aggregate functions in the DSL I'm writing. This DSL processes events in an online ...
0
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0answers
28 views

Best way to model this data, qfit or fpfit? How to get equation?

So I have this relationship, which is obviously not linear. The purpose is to see if there is (and what kind of) a relationship between FRAG (test score) and MD-R (mm^2/s). There are other covariates ...
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0answers
13 views

Significant interactions force main effects to be insignificant and plus change their sign--how to interpret? [duplicate]

I've read through many similar posts regarding significant interaction wiping out the significance of main effects, but since there were no questions regarding changing signs I decided to post another ...
0
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0answers
13 views

What type of panel regression is this

For the following equation $$ Y_{ct} = \alpha_c^D - \phi i_{ct} + \eta logx_{ct} + \epsilon_t^D + \epsilon_{ct}^D $$ where, for country c at time t, $$ Y_{ct} \text{ is the log real GDP}\ $$ ...
0
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1answer
12 views

Extracting regression coefficients [on hold]

Is there a way to extract the regression coefficients in order to plot them? Right now, we have a process where we run these in Matlab and then export the coefficients to Excel where we then chart the ...