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Questions tagged [assumptions]

Refers to the conditions under which a statistics procedure yields valid estimates and/or inference. E.g., many statistical techniques require the assumption that the data are randomly sampled in some way. Theoretical results about estimators usually require assumptions about the data generating mechanism.

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How to interpret a boxplot to check for assumptions?

This boxplot shows 5 different forms of dancing, on the y axis we have the number of injuries. This is an ANOVA model. The question is, what assumptions could not be met according to this boxplot? I ...
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Which one of these is correct for linear regression?

Only one of these is supposed to be the correct one for simple linear regression. Which pair of plots would you say has constant variance and normal distribution? I feel like none of them have both ...
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Violation of normality of residuals in glmm [duplicate]

I'm a newbie, so apologies in advance if this Q is missing any useful detail. I'm trying to test the effect of condition upon the number of times certain behaviors are produced by a group of ...
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30 views

Proof of contemporaneous exogeneity, and its implications for an AR(1) model

It can be shown by contradiction that exogeneity fails to hold for an AR(1) model. Is there any proof that contemporaneous exogeneity does not fail to hold? All I've come across is assuming it does ...
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40 views

Implications of strict exogeneity for OLS in time series

Zero Conditional Mean (ZCM), or Strict Exogeneity, is given by: $E[u|X]=0$ Equivalently, $E[u_t|X]=0, t=1,...,T$ Is it true that this implies: Zero Unconditional Mean: $E[u_t]=0, \forall t$ ...
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32 views

Why are t-tests rather than z-tests used in linear regression? [duplicate]

Do the explanatory variables need to have normal distribution in linear regression? Why are there z-tests rather than t-tests in logistic regression?
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How to verify the “random sampling” Gauss-Markov Assumption with Stata (or anything else)?

According to the book I am using, Introductory Econometrics by J.M. Wooldridge, there are 5 Gauss-Markov assumptions necessary to obtain BLUE. However, by looking in other literature, there is one ...
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42 views

Data Transformation to achieve Linearity

One assumption of OLS regression is Linearity. To check whether the assumption holds, you can plot component + residual plots or partial residual plots. When a linear relationship is apparent, is's ...
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60 views

The assumptions regarding the t-test

The t-test has an assumption that the sample provided has to be random in nature. Do we test our sample for randomness before carrying out the t-test ?
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29 views

How much Autocorrelation is acceptable in Regression Analysis?

One assumption of regression analysis is independence of residuals. I checked this assumption and found small autocorrelation (see figure). One remedy would be to incroporate dummy variables for the ...
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20 views

Variance Inflation Factor for Ridge Regression model

Is there such a thing as a metric that can determine if multicollinearity is violated in a ridge, elastic net, or lasso model? From programmatic terms, if I have a glmnet package model, is there a way ...
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Transforming panel data OLS into cross-sectional data model

I am currently stuck on a task where I am interested in estimating the production function for agricultural output using panel data as follows: \begin{equation} y_{it} = x_{it}\beta + \alpha_i + \...
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29 views

How can one verify distributional assumptions for testing procedures, if only one draw from each distribution is available

I am currently dealing with a situation in which the Wilcoxon signed rank test (WSRT) is a possible candidate to be applied to the data. So let`s say we have $n$ pairs of Random Variables $(X_i, Y_i)$ ...
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21 views

When to report the check for linear regression assumptions?

Here's the steps for an analysis. I know there is some past research implying there is a linear relationship between $Y$ and $X_1, \cdots, X_n$ So I set a hypothesis that $Y$ is a linear function of $...
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2answers
62 views

Is “joint probability” assumption necessary for regression purposes?

I state beforehand that my question may sound odd and captious (and maybe it is). In regression theory basically we assume that explanatory variables and independent variable are joined togheter ...
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1answer
55 views

whats should i do if my data is remain not normally distributed every after log, log10 [closed]

I have a dataset about body vibration; the values are not normally distributed. For that, I tried the normal log, log10, but it remains not normally distributed. What should I do?
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32 views

Is it okay to use non-parametric tests on normalized data?

I'm doing experiments with 3 conditions: A, B, and C. I have done the experiment 3 times, so each condition gets 3 values for a total of 9 values. Each value is actually an average of 5 measurements. ...
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Proportional Hazards Assumption for Frailties in Multilevel Cox Model

I'm investigating patients' mortality after a trauma based on country-wide data. In particular, I want to know if there is variation between regions within the country. Therefore, I want to employ a ...
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29 views

Normality assumption for Chi Square goodness of fit

Does Chi Square goodness of fit require normality assumption? Is it a parameteric or non-parametric test? What it its relation with t-test (parametric test) and u-test (non-parametric test)?
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51 views

Proportional odds assumption for multilevel data

I'm running model in which I analyze salary of recent graduates. People graduated from different majors and in different years. The dependent variable (salary) is measured using intervals, e.g., "less ...
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20 views

How to test multiple regression assumptions when multiple imputation has been used?

I used multiple imputation on SPSS to deal with missing data in my study. I then carried out multiple regression from the imputed and original data-sets, using a split-file. I now have output for each ...
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What is the difference between $E[\varepsilon\mid X]=0$ and $E[\varepsilon X]=0$ in OLS regression?

Why is the assumption $E[\varepsilon X]=0$ weaker than $E[\varepsilon\mid X]=0$?
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Is it legitimate to dummy code dependent variables in a mixed ANOVA? [duplicate]

Would it be legitimate to use dummy coded dependent variables in a mixed ANOVA, given that a general linear model can be seen as a form of regression (where this would be appropriate), given that the ...
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Is there an assumption of consistent scores across related items in parametric statistics?

I think there in an assumption in parametric statistics that if a participant scores high in an item, he/she is expected to score high in other items; is there a terminology regarding this? Or am I ...
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Family of GLM represents the distribution of the response variable or residuals?

I have been discussing with several lab members about this one, and we have gone to several sources but still don't quite have the answer: When we say a GLM has a family of poisson let's say are we ...
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1answer
26 views

Distributional assumption for a VAR model: is normality needed?

Do all variables in a VAR (Vector Autoregressive model) need to be normally distributed? Or there is no restriction about the distributions of the variables in this model (normal or otherwise)?
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38 views

z-test of proportions vs chi-squared

A 2-sample z-test of proportions and a chi-squared test can both be used to analyze a $2\times 2$ contingency table. In fact, for $2\times 2$, $\chi^2=z^2$. Why can the same table, being used with two ...
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25 views

Multivariate Normality ANOVA test

ANOVA requires multivariate normality as a key assumption. I understand that this assumption can be tested in MANOVA using the Mardia test, Royston test, and Henze-Zirkler test. This can be ...
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1answer
240 views

Ways of Testing Linearity Assumption in Multiple Regression apart from Residual Plots

I was going through the assumptions of linear regression and of course one of them was linearity between the dependent and the independent variables - to be precise I should say that the assumption is ...
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1answer
62 views

Does 'Conditional Independence' means there should be no multicollinearity among features?

I was reading the Naive Bayes article on Wikipedia and I read that, In Naive Bayes, the naive assumption that Naive Bayes make is "each feature is conditionally independent of every other feature, ...
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1answer
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Repeated measures factorial assessed using planned contrasts

I have dependent data that can be arrayed as a factorial. I understand that although factorials can be assessed through ANOVA, it is not necessary or always desirable to do so. A second option is 1-...
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2answers
40 views

Checking the Assumptions for T-tests

I am in the porcess of checking the assumptions of some data in order to perform a T-Test and had a few questions about how they should be set up. I was able to find the assumptions for a T-test here....
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211 views

Assumption of homoscedasticity/equal variance violated in a 2-way ANOVA

I'm analyzing results from an experiment where 56 samples were tested for a specific response to electrical stimulation. Electrical stimulation was done at 2 different stimulation frequencies, and at ...
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ANCOVA - Non-linearity of covariate

I have a dataset where I calculated genetic distances between populations of some animals (a continuous variable). I want to know if these differences are explained by physical or/and ecological ...
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Why are statistical assumptions not reported in published journal articles?

In universitiy theses I often see students including details about their model in the appendix (distribution residuals, heteroscedasticity, durbin watson, multicolinearity values). However in ...
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When are the linear regression parameters of Y and X the same as the parameters of Y' and X'?

I am working on some simple linear modeling of a physical system and assumed that taking the derivative of an equation $$Y = \beta_1 + \beta_2 X + \varepsilon$$ would give me $$\frac{dY}{dt} = \...
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1answer
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Poisson assumptions

I am dealing with a dependent variable that is either 0, 1 or 2 in theory it is unbounded and it can take values more than 2 so I am motivated to test Poisson model first. The frequency counts for ...
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confusion about the link between residuals, error terms, sample size and CLT in ANOVA

I feel a little confused about the assumption of the ANOVA and what it ensures mathematically the errors have to be iid and normally distributed N(0,1). independance of observation. Is it not a ...
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2answers
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Is it possible to derive joint probabilities from marginals with assumptions about the conditionals?

I understand the title is too generic. I tried to look for similar questions and although there were a few that were seemingly about the same issue, either they provided answers in the negative or had ...
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What is the need of assumptions in linear regression?

In linear regression, we make the following assumptions The mean of the response, $E(Y_i)$, at each set of values of the predictors, $(x_{1i}, x_{2i},…)$, is a Linear function of the predictors. The ...
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1answer
144 views

How to account for multiple measurements of same person in either two-group comparision or regression?

I am running analysis on clinical data collected from patients which are correlated either by time (longitudinally) or more commonly different measurements of the same person at same time (eg. ...
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Friedman test when subjects are not a random sample from a population/ when subjects are dependent

Imagine that you measure all $n$ people from a school class in $k$ $\geq2$ different treatment conditions. My goal is to find out whether the there is a systematic difference in Ranks (i.e. the $H_0$ ...
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1answer
46 views

Multicollinearity and predictive performance

Looking at this statement: "Multicollinearity does not affect the predictive power but individual predictor variable’s impact on the response variable could be calculated wrongly." Is this ...
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1answer
37 views

Which model assumptions are important for prediction?

Disguised as other questions, there are frequent questions where the OP checks for violations of model assumptions (e.g. normality, homogeneity of variance in linear regression) in models they intend ...
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What should I do about this regression analysis?

I did regression analysis. It's about incoming calls and amount of orders. I got a result like this. summary(ireg) Call: lm(formula = 1/sqrt(ie) ~ ia + id) Residuals: ...
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49 views

Can I fit a GLMM to near-ceiling binary accuracy data?

tl;dr Can I draw inferences from this binary response data with a ceiling effect, or is it too skewed? How do I check if the model is acceptable? I would like to analyse some binary response ...
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1answer
125 views

Assumptions of the Friedman Rank Test

Let $X_i:= (X_{i,1}, ..., X_{i,k}) $ for $i =1...n$ be $\mathbb{R}^k$-valued random Variables with $k\geq2$. I wonder what the exact assumptions are to apply the Friedman test to Realisations of ...
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81 views

Regression assumption

I have a data set where $100$ people made $500$ trips for $5$ days. I want to build a trip-level regression (zero-inflated Poisson) where the dependent variable will be the count of hard-braking in ...
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1answer
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Assumption tests to be run on each independent variable or on the entire model in a multiple linear regression?

Here are important assumptions that one has to check when performing a linear Assumption 1: Homoscedasticity of residuals or equal variance (with Breusch-Pagan test for example) Assumption 2: ...
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Assumption of ARIMA and relation to ARCH/GARCH model?

I only have a very basic understanding of time series analysis. As I am learning ARIMA and then ARCH/GARCH models, I have some subtle (at least for me) questions on the common procedure to build such ...