Questions tagged [predictor]

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, regressor variable, covariate, etc. This tag can be used for any of these synonymous terms.

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3
votes
3answers
269 views

How to tell when factors “disagree” in linear regression to produce noisy predictions?

I use a regression as my predictor. Let's say my regression is $y = a_1 x_1 + a_2 x_2 + a_3 x_3$ I realized that in practice, when my prediction is way off, it's usually because one factor ...
6
votes
1answer
247 views

Using ordinal regression to evaluate predictor “importance”?

We've got a construct-likert-scale with an internal (8 items) and an external dimension (6 item) and there is also a 5-point item y assessing the "subjective" perception (How skilled do you think you ...
1
vote
1answer
360 views

Interpolating between models in ROC space

Suppose I have two models $A$ an $B$ that predict class labels. If these give binary predictions, these will appear as pairs of (false positive rate, true positive rate) in the ROC space. We should be ...
11
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3answers
42k views

Why would one use age-squared as a covariate in a genetic association study?

Why would one use age and age-squared as covariates in a genetic association study? I can understand the use of age if it has been identified as a significant covariate, but I am at a loss as to the ...
52
votes
6answers
50k views

What is the difference between estimation and prediction?

For example, I have historical loss data and I am calculating extreme quantiles (Value-at-Risk or Probable Maximum Loss). The results obtained is for estimating the loss or predicting them? Where can ...
5
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3answers
2k views

Should a predictor, significant on its own but not with other predictors, be included in an overall multinomial logistic regression?

I constructed a model via multinominal logistic regression analysis. The final model contains three predictors. All predictors are significant when they are the only predictors. However, the ...
6
votes
2answers
5k views

What methods to use for statistical prediction/forecast of trading data?

I’m working on a trading system and need to apply some statistics on the results. Unfortunately I forgot all about statistics after I left university over a decade ago and now I really have no clue ...
4
votes
1answer
321 views

How do I create a predictor for a time series once I've confirmed Granger-causality?

I have a set of time series data that I've found granger-causality (i.e. regressed Y vs. X, X-1, Y-1), and am wondering how I can create a predictor from this linear model? Is it simply the ...
19
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4answers
87k views

Maximum number of independent variables that can be entered into a multiple regression equation

What is the limit to the number of independent variables one may enter in a multiple regression equation? I have 10 predictors that I would like to examine in terms of their relative contribution to ...
4
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1answer
2k views

Should quantitative predictors be transformed to be normally distributed?

I am always struggling with normality testing for quantitative predictors (no factors) and transforming them to normality. If I am running a GLMM and my predictors are really non-normal, should I ...
6
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2answers
1k views

When to transform predictors in regression when response may be quadratic?

I am analyzing data from an experiment in which treatment levels increase quadratically, e.g. the treatment levels are $0, 1, 4, 9$. When analyzing the response using regression, would it make sense ...
13
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4answers
3k views

Comparing importance of different sets of predictors

I was advising a research student with a particular problem, and I was keen to get the input of others on this site. Context: The researcher had three types of predictor variables. Each type ...
38
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2answers
43k views

When and how to use standardized explanatory variables in linear regression

I have 2 simple questions about linear regression: When is it advised to standardize the explanatory variables? Once estimation is carried out with standardized values, how can one predict with new ...
5
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2answers
264 views

Chi-square analog for context-dependent distributions

Lets imagine that we have some experiments. Each experiment may result in one of the outcomes: A, B, C. So we have probabilities distribution for each experiment $P_A, P_B, P_C$ which is context-...
33
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3answers
49k views

Regression coefficients that flip sign after including other predictors

Imagine You run a linear regression with four numeric predictors (IV1, ..., IV4) When only IV1 is included as a predictor the standardised beta is +.20 When you ...

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