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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True or false and why true and why false [closed]

i) In the presence of multicollinearity, the variance of OLS estimators are quite fine only that t and F test are highly misleading. ii) Forecast is the quantitative estimation of the likelihood of ...
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Mixed Model testing difference between groups and interpretation of assumptions?

I am a student looking at the annual growth for a species and trying to determine if there is a difference between the growth back in time (with time divided into different time groups (30 IDs/25% of ...
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Linear Regression Model assumptions

I am trying to understand wether I am allowed to do a linear regression or if I am not respecting some assumptions. It is my understanding that it is possible to confirm all assumptions by looking at ...
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F-test and violated assumptions

I am researching the effect of parameters on energy consumption. To determine the effect of parameters, I want to use the R Studio's F-test. In this way I want to investigate if the model with the ...
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What are the assumptions of the Cochran-Armitage test for trend?

I have actually three questions about the Cochran-Armitage test for trend, which tests for an association between a binary variable and an ordinal one: Is it valid if the expected cell count is low (&...
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How to use side-by-side boxplots to assess assumptions of a 2 sample test?

Here is the context: So we can analyse this using a 2 sample t tests. The assumptions of t-test comparing the means of two independent samples are populations being compared should follow normal ...
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2 votes
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Does the assumption of “independent and identically distributed” apply to the actual sample data or the sampling process?

While studying statistics, I came across the concept of “independent and identically distributed random variables” or IID. I’m confused as to what that applies to in practice, mainly, does it apply to ...
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Checking assumptions of Mixed Models with R code

Context and current approach: I read through quite a few posts on this website and on the internet but I'm still not 100% sure on what exactly the assumptions are and how to check them in practice. ...
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What are the assumptions of repeated measures ANCOVA?

In my experiment I have a randomly allocated control and experimental group, as well as pretest and posttest. To control for baseline differences, I saw that conducting an ANCOVA is recommended. ...
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9 votes
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What are the k-means algorithm assumptions?

I'm trying to understand what are the assumptions/hypothesis underlying the k-means clustering algorythm; specifically, I'm looking for a research/academic paper listing such hypothesis and explaining ...
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Assumptions in logistic regression for applying LRT and AIC criteria

I have a question. Do the following assumptions in logistic regression Linearity between the log-odds and the continuous covariates Non multicollinearity Absence of outliers need to be satisfied ...
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Objective criteria for assumption violations that do not utilize p-values?

Suppose we have a standard regression model and want to identify whether we have violated the assumptions of the model. Traditionally, we might utilize a significance test to determine whether (for ...
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Replicating a study with a discrete dependent variable in linear mixed effects model (1-4 scores) [duplicate]

As the title says, I want to replicate a study that runs linear mixed effects models with a dependent variable that is discrete, with scores from 1 to 4. So, I have two main questions about that. 1 ) ...
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1 answer
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Appropriateness of including control variables in lmer as random effects

I am trying to find out the effects of the condition (3 levels) on the dependent variable (intention to use a certain mode of transportation; assumed to be continuous, 1-7 scale), whilst controlling ...
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7 votes
1 answer
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Why does log-linear analysis seem to ignore the Poisson regression equidispersion assumption?

As far as I understand it, log-linear analysis is based on the use of a Poisson regression. This is what I understood from various online resources, like this online tutorial or this text whose intro ...
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Logistic regression with counts over sliding windows of time

I am working on a logistic regression model that attempts to predict failure events in the following year over a lot of devices (say 1000) using the previous number of minor incidents that happen in ...
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If the error terms in a regression setting are not observed, how can we ensure they're normally distributed?

According to the G-M assumptions, we should assume spherical errors. But my understanding is the errors -- as measured by the vertical distance from the true line of best fit to the response ...
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Do spatial regression models hold the assumption of linearity?

I'm running a spatial regression model (probably spatial durbin error model or spatial durbin model) and one of the explanatory continuous variables has a lot of (true) zeros. I'm worried that the ...
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homoscedasticity violated or not?

I was wondering if the homoscedasticity in these two figures has been violated or not? Best regards, Elise
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Compositional data analysis with rounded values: validity of log ratio methods

I want to use histopathology compositional data with percentage rounded in 10% increments (for example 4 classes percentages: 0% - 50% - 30% - 20%). I am interested in data exploration (e.g. PCA, CCA) ...
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Have my assumptions been met?

I am running assumptions for multiple regression and scatterplots are a real bane of mine. Can anyone advise as to whether the following scatterplot provides a linear or non linear relationship ...
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Comparing proportions when samples overlap

I would like to compare the proportion of people using a facility who are female with the proportion of people who live in the area that are female. The goal is to determine if women are over or ...
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2x2 contingency table with some data-points paired and some independent

There are two items in a task (item A, item B). On each of the two items participant can score success (1), failure (0), or not provide a meaningful answer (NA). Participants with NA on both item are ...
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Predicting an interaction between a covariate and an IV in a fully within-subjects design

My design is 2x2 repeated measures ancova, and I'm predicting an interaction between one of my within subjects independent variables (IV) and a fixed covariate (CV). My question is what this means for ...
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Linearity assumptions

I am doing a multiple regression analysis with 5 controlling variables, and I have many models (some of them are significant and some are not). For the reporting, should I test the regression ...
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How can i check homoscedasticity for Level-2(between)-residuals in a twolevel model?

i have specified a random intercepts and slopes model with a Level 2-predictor for the intercepts on the between level. I have done the estimation with the lme4 package in R. Now, i want to plot the ...
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Linear regression assumptions violated

I have an independent variable hours/day sitting and a dependent variable test scores, I think all of the assumptions of linear regression are violated, as in the pictures that I added So I did one ...
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Is the non-multicollinearity assumption for OLS multiple regression just an assumption of convenience?

The four assumptions for bivariate regression are:     • (L)inearity     • (I)ndepdent observations     • (N)ormal errors     • (E)qual variance And for multiple regression we add a fifth assumption:  ...
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Assumption of independence of observations and data per year in linear regression

I'm doing a linear regression model with data from 30 cities over 5 years (150 observations). However, by using data from cities over time, am I violating the assumption of independence of ...
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2 votes
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What assumptions need to be met for a hormesis model in R?

I conducted a toxicology study where I exposed fish to 6 concentrations of an effluent treatment for 10 days. At the end of the experiment, I measured 10 endpoints with the fish plasma to determine ...
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How to handle assumptions of statistical tests?

Does any definitive work exist, e.g. a review, a book chapter, or a book, on the advantages and disadvantages of existing approaches? Is there a consensus on which approach is the right one? I have ...
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understanding "independent" term in "independent and identically distributed" (iid) statement

I understand independent as the random variable values in a data aren't connected to each other in any way. (q1) Is my understanding ok? data_1: a product which has a design defect has been sold to ...
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Random effects tobit if random effects are non-normal distributed

I have the following (panel tobit) data-generating process: $y_{i, t}^* = a + bx_{i,t} + u_{i} + e_{i,t}$ $y_{i,t} = y_{i, t}^*$ if $y_{i, t}^* \geq 0$ and $y_{i,t} = 0$ otherwise. where $i = 1,..., N;...
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2 votes
2 answers
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Asymptotic T-test validity for proportion values

I have a large sample of values, bounded in $[0, 1]$, divided into two conditions A and B, and I want to test the significance of one condition A having higher value than condition B. For the details, ...
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Significant interaction in robust ANOVA but no significance in traditional ANOVA

In a 2x2 mixed design (2 groups measured at 2 times, n1 = 10, n2 = 12), a subsample violated the assumption of normality (Shapiro Wilk test). Thus, I used robust ANOVA (R-package ...
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How to check violations of assumptions for mediation models and correlations in R?

I'm not sure if I've completely misunderstood how violations of assumptions are checked. I understand that we can obtain diagnostic plots for linear models with: ...
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Do time intervals have to be consistant for a Markov chain?

My set up is as follows. I have about 50 groups of people who move about 5 states. One of these states is essentially "not-doing anything". I have their states recorded at the time-scale of ...
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Tukey-Anscombe Plot

I have fitted a mixed model for repeated measurements with three factors (2x2x3). ...
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What is the relevance of the underlying conditions for Linear Regression? [duplicate]

It is a fact that Linear Regression has certain underlying conditions that need to be taken care of. However, one striking question that comes across my mind when I say this is; WHEN? In what context ...
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3 votes
2 answers
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Regression assumption violation: lagged dependent variable as regressor

I am studying regression and a bit lost with conceptually understanding why having an independent variable correlated with the error term is a regression assumption violation. Just to give more ...
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R: Assumptions for GLM model (binomial family, logit link)

I want to explain the absence or the presence of a task by the condition of my participants Response variable: "Task" = 0 or 1 I use a GLM mixed model ( because of repeated measures): ...
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Is there a difference between perfect collinearity and multicollinearity?

I've read that for multiple regression analysis there is an assumption of no perfect collinearity. Is that the same as multicollinearity?
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Can we objectively determine whether assumptions have been violated in R?

I'm testing statistical assumptions in R and so far I've been using plot(model, which = c(1:6)), which produces six graphs for linearity, normality of errors, ...
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1 vote
1 answer
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GARCH model sensitivity to distribution assumptions

I am trying to fit an ARMA(4,4)- GARCH(1,1) model to return data, where the distribution of returns is highly leptokurtic. I plan to see whether autocorrelations exist in the data even after ...
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Assumptions in Multiple linear regression [duplicate]

Is the following assumption in MLR (multiple linear regression) true or false ?? $\epsilon_i$ is independent of $Y_i$ for i=1,…,n. Where, $\epsilon_i$ is the random error in the model $Y_i$ is the ...
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4 votes
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Linearity assumption violated - can I still draw conclusions from my model?

I am using Multiple Linear Regression to assess the impact of two predictors on Y and, especially, whether during a certain time there is an impact on ...
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The RD design. covariate balance and controlling for the covariate

Assume a standard continuity (or local randomization) based RD design where the outcome is not balanced around the cutoff with respect to a covariate. This violates the RD design because the outcome ...
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1 vote
1 answer
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Testing for statistical significance of the true positive detection rate between different machine learning models

Background Currently I am working on true positive detection for an image analysis problem. I have 4 methods and would like to test which methods differ from each other. Description of Data For each ...
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Can we predict a predictor of an outcome within a specific outcome group only?

I have number of predictors A, B, C,...X and outcome "CURE". Among 600 observations, 30% of patients had "CURE" X is a continuous variable from 0 to 30, normally distributed, ...
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1 vote
2 answers
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What are the assumptions of MLE and how to test them using residuals?

When using ordinary least square (OLS) method, there are certain residual diagnostics that need to be performed. In a similar manner, what diagnostics should be performed when using Maximum Likelihood ...
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