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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 ...

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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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15 views

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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18 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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1answer
24 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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10 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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15 views

Problem of multiple testing when checking the assumptions of a particular test

I have two sets of measures and I'd like to check whether the two samples come from the populations with the equal means. In order to choose the right test, I should first check a few things, such as: ...
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1answer
59 views

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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11 views

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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14 views

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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2answers
372 views

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
19 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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33 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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17 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
106 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
44 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
8 views

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
33 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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1answer
107 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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22 views

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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47 views

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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2answers
56 views

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
46 views

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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30 views

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
106 views

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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5answers
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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
124 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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13 views

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
39 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
36 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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25 views

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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44 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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13 views

Bayesian Additive Regression Trees - model assumptions?

BART builds on regression and classification tree models, and you can use it for continuous and binary outcomes (=probit). See Chipman 2010 for details. With normal regression methods there are a ...
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1answer
83 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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2answers
74 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
19 views

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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1answer
55 views

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 ...
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134 views

Evaluating Mann-Kendall trend test assumptions

Disclaimer: I don't have very much statistics experience.. I do have yearly climate data (yearly max temperature, total yearly precipitation...) for 200 years and want to perform the Mann-Kendall ...
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56 views

What happens with Mahalanobis-Distance, when the assumption of equal Covariance-Matrices breaks down

Assume that we want to compare the forecast quality of various forecasters $f$ on $n$ values such as stock-market prices or whatever. We could then define a "Mahalanobis-Distance" (MD) (or rather ...
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22 views

Deviations from normal distribution

I'm conducting multiple regression analyses using a sample of around 1200 participants. I'm first trying to identify relevant covariates to include in my model, in which I'm using ANOVA, t-tests, and ...
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23 views

Does sample size needs to be consider in the correlation between a proportion and a ranked variable?

I'm looking for the correlation between a rank variable A and the proportion of blue (variable B) among 3 types of colour: blue, ...
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27 views

Levene's test significant in 2x3 mixed design ANOVA

I'm trying to run a 2x3 mixed design ANOVA. Participants were measured on three different domains at two different times. One out of the 6 sets of results violates Levene's test while the rest do not. ...
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1answer
38 views

bayesian analysis on normal distribution - robustness of the variance

I am doing bayesian inference on normal data, and wonder how robust are the results with respects to some assumptions and potential mistakes. Specifically, for simplicity I want to assume that ...
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1answer
59 views

Assumptions of path analysis when multivariate normal distribution is violated

I'm creating my first path analysis model with lavaan (R package). The assumption of multivariate normal distribution, however, is violated. Also, in the regression M1 ~ X1 + X2 (mediator ~ exogenous ...
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32 views

What are the assumptions of multi-level modelling and how to test?

I've been struggling to find out what the assumptions of multi-level modelling. The textbook I have starts saying you can ignore homoscedacity and independence now at the beginning of the chapter, and ...
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26 views

Stable seasonality F-test does not meet assumptions for one way ANOVA

I am having trouble to understand Stable seasonality F-test. I know it is basically the same test as one way ANOVA, but the assumptions for one way ANOVA can´t be met for it. For ANOVA the data should ...
3
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1answer
27 views

How to check if the random effects in a random effect model are uncorrelated with the input variables?

Some asked before "Why do random effect models require the effects to be uncorrelated with the input variables, while fixed effect models allow correlation?" My question is: how do you check this ...
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1answer
54 views

Most relaxed assumptions to get consistency of linear regression?

What are the most relaxed assumptions to get consistency of the linear regression estimates with $p$ variables? The most basic assumptions that I know are in White (1984): 1) The model is correct 2)...
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85 views

Need help with my MANOVA

First a short description of my dataset: I have 8 independent binary variables with the values 0 and 1 (say something about characteristics of the subject line of an e-mail) I have 7 dependent ...
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1answer
53 views

What is the meaning of “The assumptions of the regression model are satisfied”? [closed]

I still can't get it. I think that if the assumptions are satisfied, the model is right. But what is the meaning of "right model"?
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29 views

Mixed-Effects Model Assumption with Different Variance Structure

If I was building a linear mixed-effects model and I changed the variance structure (let's say to a power function) to represent an increasing variance over time points, would the assumption of ...