Refers to the variables used in a model to predict a response. This tag can also be used for $X$ variables in explanatory & descriptive modeling, not just predictive modeling. This same construct goes by many names in different contexts, including: independent variable, explanatory variable, ...

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30 views

Exclude not important predictors from dataset or leave them all?

I have a large dataset with 6 predictors, with a goal to predict bank loan interest, based on year income, time at work, loan amount, credit balance, credit utilization rate, etc. I use python with ...
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14 views

Combine multiple independent variables into one variable in a GLM/GAM/GAMLSS model

In the R package gamlss there is a function centiles that according to the documentation is ...
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13 views

Should I use GEE, Multilevel or Cox regression?

I am interested in the relationship between the number of hours worked per week and the chances of getting an illness. My dataset consists of 47 subjects, the predictor variable hours worked per week ...
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23 views

An independent variable in the logistic regression has 2.2%, 2.1% and 95.7% distribution [closed]

I have one independent variable in the logistic regression with a 2.2%, 2.1% and 95.7% distribution (three categories IV). My DV has good distribution (68% and 32%). How would this IV affect my ...
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35 views

Is feature complementarity different from feature interaction?

I am writing a conference paper in which I have a sentence like "...complementary/interactive features...". This sentence ...
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43 views

In regression, what is the limit of independent variables?

After having taken the Coursera Data Science specialization, I am faced with my first "practical" problem which I plan on solving with some sort of regression. This is my first real world, ...
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11 views

Active independent variable

In a study, there are two independent variables - A and B. We only manipulate variable B. Do we count A as an independent variable in our analysis, even though it has not been manipulated?
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19 views

Testing to Compare for “Impact” of Independent Variable on Dependent Variable

How can I perform a statistical test to judge impact of an independent variable on a dependent variable given multiple regression output? In the example below, how would I test if gender or work ...
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12 views

Evaluating a pretreatment predictor with repeated measures ordinal data

I am currently attempting to study whether particular baseline factors predict pre/post changes in relation to a substance use intervention. However, a few things have me stumped. Our substance use ...
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30 views

Positive and negative impact of predictors on responses in data mining models

My question is an extension to the question asked here. How does one identify the parity of predictor/feature/variable impact on response/outcome in a data mining model. Is there a standard procedure ...
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36 views

How “bad” is it to use an independent variable as part of a proxy dependent variable in forecasting?

I am fitting a logistic regression model in order to forecast the occurrence of an event. Let the event I am interested in forecasting $Y$ be whether or not someone purchases stock in a given company ...
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10 views

Modelling Zip-Code Level Demographic Data and Individual-Level Data

Suppose you have a dataset with numerous individual-specific variables, such as relationship length, product usage, zip code etc., as well as a dataset with zip-code specific information, such as ...
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17 views

what are the independent and the dependent variables to establish the test i need for hypothesis testing?

The data looks like this Actually the dataset has 4 levels, each level being a roll up of the original dataset A <- being rolled at a separate levels A - original B - clubbed all products for ...
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34 views

What's an example of a best linear predictor that's not a best predictor?

I just learned about the definition of a best linear predictor found by minimization of variance of $Y$ given $X$, or in other words trying to minimize the variance of ...
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12 views

Explanatory variable and the connection between them

What is the statistical term for two explanatory variables that when adding one of them into the estimation the other become insignificant while the first is statistically significant? So there is a ...
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3answers
146 views

Regression models: cases per independent variable?

In logistic regression and cox regression, a general recommendation is to include a maximum of one independent variable (IV) for every 10 events in order to avoid overfitting. I have seen some studies ...
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21 views

Repeated predictor in a CHAID tree

I'm trying to explain a variable (a mobility profile) thanks to predictors (for example age, gender, driver license, etc.) in a group of people. I'm using the CHAID algorithm with R. In the decision ...
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1answer
33 views

How to Include an Independent Variable with one-half 0s, one-half non-0 values

I am running a negative binomial regression. One of my independent variables is a measure of distance traveled - half of the observations are 0 because they do not travel, while the other half have a ...
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35 views

Right-censored independent variable in Cox/logistic regression

I have a right-censored continuous independent variable that I want to include in a Cox regression. The variable is a physiologic test which is capped at a certain time, say 120 seconds, due to safety ...
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18 views

Minimizer of a function containing response and predicting variables

Can anyone please give me the expression of the "minimizer" of $$\sum_{i = 1}^n \vert y_i - b x_i \vert + \sum_{i = 1}^n (y_i - b x_i)^2 \quad \quad ?$$ I am unable to find this expression on the ...
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66 views

Reason why dependent variables need to be interval type and independent variables need to be categorical type when finding differences in group means?

Can someone explain the basics about why dependent variables need to be interval type and independent variables need to be categorical type when finding differences in group means? The responses I ...
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2answers
61 views

Two variables significant independently, but only one in a model?

I want to see how temperature and precipitation correlate with number of fires. If i do correlations independently, both are statistically significant, r(temp)=0.5, p<0.05, r(precip)=-0.3, ...
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26 views

Identifying the dependent variable in logistic regression

I am writing a critique on a research paper and am confused about which one is my dependent variable. The study investigates patient-to nurse ratio and its effects on mortality, failure-to-rescue, ...
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37 views

How to eliminate noise variables when using ensemble prediction methods like randomGLM in R?

The task involves predicting a binary outcome in a small data set (sample sizes of 20-70) using many (>100) variables as potential predictors. The main problem is that the number of predictors is much ...
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1answer
161 views

Which method (enter, Forward LR or Backward LR) of logistic regression to use?

My study is a prospective observational study. My dependent variable (outcome) is development of surgical site infection (SSI) after surgery and my independent variables (predictors) are many factors ...
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2answers
185 views

Regress IV on DV, or DV on IV?

This is a question about statistical language. Do you regress the IV on the DV, or do you regress the DV on the IV? Which is the correct way of saying this?
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81 views

Linear Minimum Mean Squared Error Estimate (LMMSE) predictor for an MA(3) process

A moving average (MA) process is described by $X[n]=\sum_{k=0}^{L}d_kW_{n-k}$ Such a process is denoted MA(L) and is said to be of order L. The input W[n] is an independent random sequence. Find ...
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18 views

Expectation for number of stops

I was looking through old exam questions and stumbled upon a question in Henk Tijim's Probability Exam Questions and Solutions that rocked me, so I began to think of further questions. Here is the ...
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1answer
15 views

Best set of variables in linear regression when the response is repeated

I have monthly data about customer care in a bank branch. The variables are presented as follows: Global evaluation: expressed in percentages. X1, X2, ... X14 : Yes or no questions taken from a ...
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43 views

Increasing data leads to poorer performance

First, I'm new at Machine Learning, but I'm having to drink from the firehose while implementing. I have truck-loads of parsed timeseries data for thousands of subjects, from which I'm trying to ...
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28 views

Simple linear regression where the exact measurement error is known

I've been looking through a bunch of error-in-variables models, but I can't find one that matches what I'm looking for (if it exists). I am trying to do a simple (univariate) linear regression where ...
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1answer
75 views

Calculating effect & CI of continuous variable when class covariates are set to their mean

I'm trying to plot the effect of a continuous variable (VAR1) on the response from a Generalized Linear Mixed Model. In other words, I'd like to predict the response y when VAR1 is x, setting all ...
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1answer
86 views

prediction on short time series with seasonality and data correlations

I have, say, 5 weeks of data standing for daily income of a company and I want to predict the next income. Obviously, there is a seasonality in data - every day is "seasonal" with the same day of the ...
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28 views

Getting lagged values of indep. variables to model contemporaneous values of the dep. variable

I am trying to forecast the variable, oenb_dependent: My current sample data looks like that: ...
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23 views

Generalizes Estimating Equations (GEE): How many factors are too many? [closed]

how many factors (independent variables) are too many when running Generalized Estimating Equations (GEE)?
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74 views

Ordinal Dependent Variable and Ordinal Independent Variable. Which test to perform analysis with?

I have a question regarding Ordinal data. I have measured 'Attitude towards a product' using Likert scale and I have measured 'Purchase Intentions to buy the product' also using Likert scale. Now I ...
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20 views

Two-period lagged effect on dependent variable due to increase in independent variable

The following time-series is given: yt = 53 + 0.4xt + 0.2xt-1 + 0.1xt-2 + 0.8yt-1 where t denotes the time period. If the is a one-time increase in x with 100 in t, what is the effect on y in period ...
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89 views

How to interpret LASSO graphs

I was given access to a total of 19 pieces of deceptive and persuasive texts along with a percentage on whether the readers of the said text followed through with the text's demands. The 19 cases ...
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2answers
60 views

Can I include two predictors (A & B) in one regression model if predictor A is dependent on B?

I want to include two predictors (total brain volume and corrected gray matter volume) into one regression model in order to predict the level of cognition (dependent variable). However, this ...
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2answers
62 views

Is it possible to compare 4 variables at once?

I have data set for one year it should looks like this example. For some points, C will be same, because they lay in same areas of concentration. ...
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1answer
31 views

Correlation or dependence between NDVI and pollution data sets

Is there any statistical test or measure to evaluation the degree of correlation or dependence between two sets of data-points ? First set is represented by NDVI values in each pixel and second set is ...
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1answer
100 views

Index-variable as an independent variable

In my regression on gdp-growth, I also want to bring in something like a "freedom"-variable, to show how free a country is (press freedom, economic freedom). now there is no number for this, except ...
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29 views

Percentage/Mixture data with many zeros

My dependent variable is continuous. My independent variables can be looked at in two ways. In the first, they are a bunch of count data with a large cluster at zero. In the second way, we can ...
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13 views

Should I include a ratio as predictor if I don't have the complete numerator?

There is a ratio 'dti' calculated using: the borrower’s 'total monthly debt payments on the total debt obligations', excluding 'mortgage and the requested loan', divided by the 'borrower’s ...
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41 views

How good is my computer aided diagnosis system vs the expert?

I have developed a systematic method that attempts to quantify the amount of disease present in medical images. E.g. % area abnormal. In my dataset, I have healthy people with no disease, and people ...
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2answers
48 views

Logistic regression on all data in order to analyze predictors

I have some experience working with classification, and in those instances we always use a training and a test set (and possibly validation sets). However, I'm currently facing a different problem. I ...
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27 views

Too small baseline predictors

I'm trying to implement a recommender system, based on SVD-algorithm. I have a matrix with binary rates, i.e. 0 and 1. This matrix is very sparse. I'm using a formula for learning process: ...
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60 views

Predictor variable relative importance in this regression

I am performing a linear regression analysis which has a continuous numeric positive value dependent variable and 7 independent variables. The independent variables include one continuous positive ...
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53 views

Any role of redundancy analysis for inclusion of predictors in regression model?

Is there any role of redundancy analysis (for example using the redun() function of the Hmisc package in R) in finding variables to be included for a regression ...
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32 views

Relative importance of predictors in the final model

A common question that frequently comes up, while presenting the findings of a predictive model to a Business audience (with non-statistical background) is - Which variable/predictor is most important ...