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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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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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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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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1answer
30 views

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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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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Correct interpretation of the zero conditional mean assumption in the linear regression model

In many books the population linear regression model $Y = \langle \beta, X \rangle + U$ has the following "zero conditional mean assumption" (here $Y,X,U$ are random variables; let's also ...
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Concept Clarification: Logistic Regression Assumption

Here is one of the assumptions under logistic regression: logistic regression assumes linearity of independent variables and log odds. I understand if this assumption is violated, we can then ...
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1answer
37 views

Independence Assumption Simulation?

I'm simulating what happens when you break the assumption of independence when you sample without replacement. The rule of thumb is that you shouldn't sample more that 10% of the population. Kahn ...
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Intuition of the log odds linearity assumption for logistic regression

I'm currently having trouble understanding the assumption of logistic regression that the input variables must be linearly related to the log odds. Specifically, what actually happens to the model ...
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Using software to apply tests under different perspectives (sets of hypotheses $(H_0, H_1)$)

I have read very useful paper "Wilcoxon-Mann-Whitney or t-test? On assumptions for hypothesis tests and multiple interpretations of decision rules" by Fay and Proschan (2010). This paper ...
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Is there an assumption-free ANOVA?

ANOVA presupposes a normal distribution and equal variance. Kruskal–Wallis (non-parametric ANOVA) assumes that all population distributions are the same (except their parameters). I'd like to know if ...
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Well-defined OLS estimator [duplicate]

we know that OLS estimator $\beta = (X'X)^{-1}X'y$ Under what conditions of the matrix X, the OLS estimator is well-defined?
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Assumptions of Mann-Whitney test for at least ordinal data

I am reading article by Divine et al. about using Mann-Whitney test for data that is at least ordinal (i.e. it may be discrete with many ties). It says the following (in section 2.3): That is, it (...
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Wilcoxon signed-rank test can be a test for comparing means but not for comparing medians?

Wikipedia says that we can rewrite the hypotheses of the one-sample Wilcoxon signed-rank test in terms of expected value (as "a test for the location of the mean") if the following ...
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Independent/unpaired t-test assumption of independent observation?

I am just wondering if unpaired/independent t-test assumes each observation is not related? For instance, in our data there were group A and B. In group B, there were 3 subjects that were observed ...
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When to check model assumptions

Statistical methods are based on model assumptions. For example, an independent one-way ANOVA makes the following assumptions: Normally distributed residuals Homogeneity of variance Independence of ...
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How to determine effect size in addition to significance in statistical inference tests that do not explicitly estimate effect size?

Students in linear regression courses are taught that more data is good. They're taught that checking assumptions are good. They're taught that the Shapiro-Wilk test is good. Then they're taught that ...
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Proving this implication of zero conditional mean assumption

I want to show that $E_{\epsilon} ( x_i \epsilon_i)=0$, where $\epsilon$ is the population error term. I want to be very careful in every step with the language, so if there is even a small mistakes ...
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GLMER levene's test significant

I am running a glmer and I checked for assumptions of normality (plotting QQ plots) and homogeneity of variances using Levene's test. My variable A is something ...
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My explanatory variable is also count data, is there a way I can still do a Poisson Regression?

I'm thinking of performing a Poisson regression on a dataset that I have. However, both the x and the y variables are based on counts. One of the assumptions related to Poisson regression is that the ...
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Machine learning (CNN) - What questions can I answer while violating assumption of independence?

Introduction to the experiment and data type: Suppose that I have 20 or so participants exposed to visual stimuli in several trials in two different conditions: Simple, and Complex, of 3 flavors each. ...
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What should we do if the anticipation effect is violated in Difference-in-Difference but parallel trend is satisfied?

In Difference-in-Difference studies, parallel trend is the main assumption, in some paper, they use other assumptions but inconsistent. For example, Borusyak,2021 used "no anticipation effect&...
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How to test assumptions for a large number of statistical tests?

I am running a logistic regression. The outcome is a clinical variable, and there are two predictors: gene expression (continuous), hormone levels (continuous), and the interaction term between them. ...
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How does data that violates linear regression assumptions (of the residuals) look?

Linear regression has two assumptions about the residuals : The residuals should have constant variance (for every level of the predictor). The residuals should follow a normal distribution. Is it ...
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Is it ok to drop a non-linear treatment level in ANCOVA?

I am running an ancova to measure differences in an allometric relationship between tree height (dependent variable) and diameter (covariate) among one nutrient treatment with 4 levels. One of the ...
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MANOVA: Dependence in dependent variables

In my study, I have two age groups (YA and OA) and 3 scores (A, B, C) are collected from each participant. Here I'm interested in two dependent variables, "RCG" which is calculated by ...
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GLM residual assumptions modelling binary response variable

I'm taking a intro to modelling course at my university. We are currently learning about modelling Binary response data. I am confused about the assumptions of the Generalised Linear Model, in R. ...
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How to check assumptions and model specifications for spatial regression analysis in Stata?

I want to run several spatial autoregressive regressions (SAR) using the "spregress" command in Stata (version 16.1). When you do non-spatial multiple OLS, several assumptions have to be met,...
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51 views

Linear mixed effect model - heteroskedascity interpretation

I have a dataset with speed difference between men and women on several race distance. The data structure look like this. ...
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63 views

What can I do to get better overlap in propensity score distributions?

I would like to verify the positivity assumption to identify causal effects from observational data. My exposure prevalence is about 6%. When I included several potential confounders in my exposure ...
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Why doesn't Logistic Regression require heteroscedasticity and normality of the residuals, neither a linear relationship?

I was reading this link when I got stuck trying to understand. Not even Wooldridge in Introductory Econometrics, or O'Reilly Data Science from Scratch explored this question. And I was surprised I ...
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Checking fixed effects regression assumptions

I have a panel data set which I have fit a fixed effects model to using plm() in R. The Hausman test indicated that a fixed effects model should be used over a ...
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Is there any difference between a Logistic Regression for inference and for prediction?

When studying Linear Regression, I remember that Multicollinearity is something that impacts inference and not prediction, at least not always. Also, I noted that the assumptions tends to be neglected ...
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How do I know if my data violate the assumption of independence?

I have data on reaction time (dependent variable, continuous) from participants viewing a visual stimulus that can have 7 different states (-3, -2, -1, 0, 1, 2, 3, independent variable, nominal). I ...
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Does linear regression have four or ten assumptions? [duplicate]

I couldn't find any topic with this discussion. Not sure if this is just too obvious and people don't even discuss, but I'll take my chances... does linear regression have four or ten assumptions? I ...
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Why doesn't a residual plot indicate whether or not the linearity assumption is violated?

I learned in stats that a residual plot is a plot of the residuals on the vertical axis and the independent variable on the horizontal axis. So basically it looks like the regression line turned ...
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29 views

What statistical tests should i use if both normality and homogenity of distribution assumptions were violated?

my (quantitative) data are divided into 4 groups: T0, n = 415 T1, n = 93 T2, n = 74 T3, n = 51 *NOTICE THE DIFFERENT GROUP SIZES! I wish to compare between the groups. Usually ANOVA would fit, however,...
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Logistic Regression - Are my observations dependent or independent depending on interpretation of the results?

I want to do logistic regression to test whether certain factors predict a loss of movement following an injury. I have measured movement from 150 muscle groups that have wounded from about 40 people. ...
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Do I need to test for assumptions before linear regression if I get good predictive results?

Do I need to test for assumptions before linear regression if I get good predictive results? Does the good results imply the assumptions are satisfied?
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Implications of using the mean of the max as a predictor in regression

What are the implications of using a predictor which has been aggregated twice (the mean of a set of max's) as a variable in a regression analysis? I'm performing a regression on the panel dataset: <...
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36 views

What are the conditions on standard GARCH coefficients

it is hard to find the full list of restrictions on GARCH(p,q) coefficients. Let me clarify. First, define GARCH(p,q) for a zero-mean returns time series as: \begin{equation} \label{eq:garch_pq} \...
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Do residuals need to be normally distributed to carry out Weighted Least Square (WLS) Regression?

First of all, I have to admit I am here because I am struggling with my dissertation. With this disclaimer out of the way, here is my problem: I am trying to carry out multiple regression analysis but ...
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Which modern robust methods should be used (under what circumstances/as a standard)? [closed]

I started reading about modern robust methods as an alternative to classic parametric techniques because I keep encountering issues with normality and, at times, violations of other classic parametric ...
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On the assumptions of Hommel, Rom and Hochberg corrections for FWER control

First of all, I looked up similar questions here before posting but those were unanswered, so I'll ask again. My major is Biology but I also hold a MSc in Bioinformatics, so it is in my best interests ...
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Is there a "Weibullity" test?

There exist several tests of normality. This is, tests for checking if a data set is normally distributed. Is there a "Test of Weibullity"? This is, a test for checking if a data set is ...
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Factor analysis with different experimental conditions: Implications(?)

I have conducted (exploratory) factor analysis (EFA) on data from a within-subject design with four different experimental conditions. Each participant goes through all conditions one after the other (...
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Interpreting linear regression diagnostic plots correctly in R

I've been trying to build a linear regression model over ~30,000 data points (sample size) and have been trying to diagnose whether the model assumptions for it are met based on this link: http://www....

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