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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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13 views

Proportion or (adjusted) count variable as regression predictor with varying denominators

I am attempting to run various different regression models for different health outcomes (i.e., ordered logit for self-rated health, Cox models for survival). My predictor variable is quality of care ...
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20 views

SEM: High SRMR in model with binary predictor. Other fit indices OK [closed]

In this post I may display severe lack of understanding in SEM and the math behind it so please be kind. I am testing the following structural model with lavaan using MLM (due to non-normality) with ...
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1answer
18 views

Including a quadratic effect for an ordinal variable in a regression analysis

It's common for many datasets to have ordinal versions of numerical variables, such as age groups (e.g. "Under 20", "20-30", "30-40", etc.) or time groups (e.g. "Less than 15 minutes", "15-30 minutes",...
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Merging dramatically different data sources

I want to analyze some data that asked the same set of survey items, but across dramatically different samples (all demographics and most other variables are statistically significantly different ...
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16 views

How to combine continuous variables for logistic regression: ratio and absolute numbers

I am trying to fit a logistic regression and I have variables which are in terms of ratios and in absolute numbers. How should I treat them? Is it okay to treat them equally, or should the absolute ...
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20 views

Determine useful predictors for logistic model [duplicate]

I have dataset at my disposal and I am suppose to run a logistic regression. What is the best way to determine which explanatory variables are useful and which are totally off? Is there any general ...
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9 views

Identify Influential predictors

I have a dataset with binary class as outcome. I was exploring the data through plotting the variables for both the classes. For example, something like below ...
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31 views

Does it make sense to fit an ARIMA model to the remainder component of a timeseries?

Suppose I have a timeseries, something like this: ...
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21 views

Cannot understand a notation detail in ESL's Statistical Decision Theory EPE minimization

In The Elements of Statistical Learning, at page 18 the authors explain that, in order to minimize the EPE (Expected Prediction Error defined as the mean of the loss function: $\text{EPE}(f) = \mathbb{...
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12 views

Does it make sense to see if success of one thing determines the success of another

I have modeled whether a bird is detected by an antenna (1=yes, 0=no) with the following predictor variables: length of visit, species, and site. Individual ID is a random effect. I am not also ...
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19 views

Multiple regression with predictors for different “directions”?

I expect predictor A to negatively predict my dependent variable, and predictor B to positively predict the dependent variable. Can I include both predictors in a (linear) multiple regression model ...
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1answer
55 views

Should I compare two models using AIC?

I calculated duration (IV) in seconds using two different ranges (0 to 5s and 0 to 10s). The aim was to find out which range contributes to higher word learning outcomes (dichotomous DV). I ...
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21 views

Which statistical method do I need for my research (combining correlation and independent two-samples t-test?) [closed]

I need some guidance with my model, because I believe I need both correlation as well as an independent two samples t-test for my research.. is that even a thing? My model claims that firm ...
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6 views

What would happen to a partial dependence plot if the assumption of independence was violated?

I understand the largest issue with PDPs is that it's assumed that the feature/s of the plot that are calculated are not correlated with other features. Let's use something like height and weight to ...
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22 views

How to quantify a parent's influence of a node in a Bayesian Network?

Consider a toy bayesian network that models purchase of items at a store. The nodes include: {Brand, Price, Purchased}. It is possible that when you marginalize over price, P(purchase|brand) may ...
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30 views

best predictor and best linear predictor

Suppose that $X$ and $Y$ are independent, each distributed as $\mathcal{B}(1, p)$, if I define $Z=X+Y$ and $W=X-Y$ how can I calculate the best predictor and the best linear predictor of $Z$ given $W$,...
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67 views

How to calculate the Bayes Estimator (Predictor) for the following problem?

Given the error function: $$ e(y,\hat{y}) = \begin{cases} 2,& \text{if } y<\hat{y}-1\\ 0,& \text{if } |y-y|\leq 1\\ 1,& \text{if } y>\hat{y}+1\\ \end{cases} $$ I need ...
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18 views

Regression by python of mixed types of variables

I have a data set contains mixed types of variables numerical variables, binary categorical {Yes,No} and categorical (very high,high, medium,small,..). It is required to apply the following scikit ...
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12 views

effects of a covariate on fixed effects interactions in a mixed models (in lme)

We measured brain responses to two stimuli (2 lvls factor condition) from two brain regions (2 lvls factor hemisphere) and measured across 4 years (4 lvls factor time). We focus on development of ...
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41 views

Can a missing independent variable from a regression model produce a flawed analysis?

I am doing a regression analysis on the various factors which influence accident levels in my city. The 2 factors used in my regression model are covariates : i) ...
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15 views

What is an example to show Wald's test does not confirm significance at the same level for each variable?

Suppose that the true model is given by Y=0.3+X1+X2+X3. Assume we have 100 training examples where each covariate vector (X1, X2, X3) is randomly drawn from some distribution P and Y is generated ...
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66 views

Conditional Expectation and Prediction

This is taken from the book "A First Course in Probability" from Sheldon Ross: Sometimes a situation arises in which the value of a random variable $X$ is observed and then, on the basis of the ...
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23 views

Deciding upon the important regressors for a SARIMA model

I have 14 months(01/07/2018 to 30/08/2019) of one minute data, which I have aggregated to 10 mins block. So I have a data of dimension "61056 * 350". From this I am using 12 months of data to train ...
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48 views

How many covariate are too many? [duplicate]

I have a sample size of 167. In addition to DV, IV, and a moderator variable, I would like to use 6 variables. Is it too many? How do you determine acceptable numbers of covariates? Also, fewer ...
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1answer
37 views

Method(s) to predict binary outcome from onset of variation in time series data

Context: I have data on 100 patients showing their time of attendance at a service. They attend on a roughly daily basis between 9-5 (except weekends and occasional missed appointments). They access a ...
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1answer
27 views

ANCOVA baseline as covariate

just a simple question, to make sure this is correct. I watched some videos with similar study questions and I'm following them. I have 4 groups of treatments(Ct+A1+A2+A3), and two different moments, ...
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1answer
75 views

Understanding predictor importance in clustering with SPSS

SPSS offers a certain metric to assess predictor or variable importance in clustering. How it is calculated has already been answered in the following thread: "How is Relative Variable Importance ...
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What are good public datasets for time series analysis with “certified” (by papers in the literature) good predictors of the target variable? [closed]

I have to test different models for time series forecasting and predictors (exogenous covariates) goodness evaluation and I would like to use datasets used in relevant scientific publications that ...
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2answers
1k views

Can someone give the intuition behind Mean Absolute Error and the Median? [duplicate]

I do not understand the intuition behind why the median is the best estimate if we are going to judge prediction accuracy using the Mean Absolute Error. Let's say you have a random variable X and you ...
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16 views

Regression variables not used/applicable for certain cases [duplicate]

I have a rank-ordered logit model in which the various independent variables are pertinent for some cases but not others. For example, cases 1, 2, 3, & 4 might have variables A & B that are ...
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1answer
52 views

Can adjusted r-squared (or r-squared) be used to compare the strength of independent variables in linear multiple regression?

Relative newbie with quantitative analysis here, so forgive me if the question is naive or ill-specified. I have argued in a manuscript that along with using Beta values in linear multiple regression ...
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1answer
23 views

time series data modeling for deep learning

what is the best format to feed the input data, which are time series with varying density over time, to a deep learning network, while at any iteration we want to feed a batch of data including a ...
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23 views

State-of-the-art ways of selecting variables for predictive models

I'd like to know about reputably reliable methods of selecting variables for predictive models based on large multivariate data sets and how they guard against spurious results (something analogous to ...
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1answer
28 views

Interactions between categorical and continuous independent variables

Im going to investigate if a disease have a negative impact on the development of children. The disease is the independent variable with additionally 10 confounders. Do I have to check for ...
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8 views

Is there a way to assess how much and in which direction a predictor is associated with class in my classifier?

I searched the forum, and couldn't find a matching question. I am building an MLP to predict an outcome (occurrence of a medical condition) in Weka. Previously I identified positive and negative ...
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9 views

How to identify important categories in categorical variable to predict some binary variable?

Imagine that we have two sets of data. The first one contains information about websites visited by certain users: ...
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1answer
55 views

binomial correlation?

I am interested in testing for a correlation between two variables, both of which are binomial. I guess this is equivalent to a Model II regression where both variables are binomial. Ideally I want ...
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1answer
24 views

Controlling for a variable: t-test or covariate?

Lets say I have some data that looks like this: ...
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1answer
128 views

Regression response and explanatory variables

I am a newbie to regression, and I was trying to answer the following question using this data. Is there a meaningful difference between the distribution of damage caused by hurricanes with ...
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29 views

Am I doing the right model? lm or lmer?

I am looking at the effect of land cover (tree species, grass, woodland) on soil carbon at 3 depths. I have site as a random factor and biomass a covariate. I ran a ranova which revealed there was no ...
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25 views

R: Modelling estimates for the factors and 'sub-factors' of a predictor variable within a GLM

To take a simple example, let's say the model contains a dichotomous predictor variable with the factors {Group X, Group Y}, where all observations can be categorized into one of the two groups. ...
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23 views

Prediction of change in response behavior in survey

I am working with a longitudinal survey with responses from three separate occasions, so far. It follows individuals in childhood and adulthood. One of the questions asked is: "Has your child ever ...
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1answer
62 views

How to interpret mixed effects logistic regression of 2 categorical predictors?

if A is the Group reference level & Noun is the Class reference level, is this summary telling us GroupC is significantly different from GroupA at only the level of nouns(intercept)? Or is it an ...
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1answer
170 views

a covariate versus a random effect [duplicate]

I have looked around on cross validated as well as other places but can't seem to find an answer. I'm running a generalized linear mixed-effects model. Y~initial abundance + Treatment + (1|Month) ...
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180 views

What do clinicians mean by “independent predictor”?

I am a biostatistician and often clinicians use the term "independent predictor". For me, it is not clear what exactly is meant by this, and my strategy has so far been to not use the term myself... ...
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1answer
33 views

How to interpret the results of multiple regression when two dummy coded predictor variables are depended?

I am would like to get the estimated influence of two conditions (variable A and variable B). When I dummy-coded variable A and B and carried out a multiple regression analysis, both of them were ...
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47 views

What do these SAS plots imply about the regression outcomes?

I have run a Tobit regression, and in the output the following charts are generated (at the end of parameter estimates). I cannot relate these charts with the parameter estimates. Could someone give ...
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7 views

Measuring effects of IV (constant) on DV

I have an independent variable (a bias) that is technically a constant. I want to measure the effects of the IV on the DV. How do I do this? I'm using SPSS. Let's say, participants produced A or B ...
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3answers
515 views

What is covariate?

I'm confused with this term: covariate. What is it? Is is just the observed outcomes of some random variables that contain information that could help us enhance our prediction of another random ...
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2answers
54 views

Is the accuracy equal if the true positive and false positive rates are equal between two groups?

I was reading the paper "Equality of Opportunity in Supervised Learning" (link). In that paper there is a feature $A \in \{0,1\}$ and a binary outcome $y \in \{0,1\}$. The population is divided into ...