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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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Does the t-test require randomization?

Can I use t test for a non-equivalent quasi-experimemtal design? As there is no randomization, can it violate the assumptions of the t-test? What statistical technique should I use?
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Problem from Introductory Wooldridge regarding WLS

I was reading the book introductory econometrics by "Wooldridge", and in Chapter 8 (Heteroscedasticity), it is stated that (see pink part) I could not understand, if $u$ and $x$ are uncorrelated, ...
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Asymptotic exactness of Welch's t-test under arbitrary distributions

A common recommendation when using the Welch t-test for comparing two unpaired sample means is that the assumption of normality is not a problem when the sample size $n$ is bigger than some constant $...
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Do the assumptions for linear regression apply to AR(p) models?

If we have a stationary time series and we want to model it as an AR(p) process, what conditions must hold besides the stationarity itself? Are they the same a the assumptions for linear regression: ...
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Validity of the linearity assumption

I have to research unaided recall of commercials given a set of variables. So, I formulated the following model: $unaided = \beta_0 + \beta_1duration + \beta_2blocksize + \beta_3position + \beta_4 ...
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Error term conditional mean of 0. Linear regression

From my econometrics book i understand that the most important assumption of linear regression is that the error term has a conditional mean of 0, thus is independent of all the x values. How can i ...
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26 views

How to interpret plot residuals vs fitted values?

I run a ols regression and want now check the linearity assumption. I found out that i have to plot the residuals vs the fitted values and if there is no non linear pattern the linearity assumption ...
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29 views

How to check if a data is poisson sampled?

I was reading one article which develops a theory for the Poisson sampled data. That is the data is collected over time-points $\{T_k, k>1\}$, which are jump-moments of a homogeneous Poisson ...
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Assumption testing for a large amount of individual regression models and averaging R-squared?

I am running the following model for my thesis, a simple regression: \begin{equation} y_{i,t} = \alpha_t+\beta_tx_{p,t}+\varepsilon_{i,t} \end{equation} where Y is an observed variable (...
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What are the validity test of the Maximum likelihood estimation?

I know that the OLS has the standard validity test for assumption violation but when it come to the MLE how can we tell that the coefficients are valid for the conclusion
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100 views

Model assumption of linearity

I am trying to interpret the outcome of a test for assumption of linearity. This is the dataframe: ...
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47 views

10% rule for sample sizes

In an introductory stats book by Nicole Radziwell "Statistics the easy way with R" , an assumption used for nearly every statistical test (e.g.t-tets, anova, etc) is that the sample size should not ...
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Gaussian Processes: A Crucial Assumption?

I'm reading this paper, and I've come to what seems to be a pretty crucial assumption: Now, the n observations in an arbitrary data set, y = {y1, . . . , yn}, can always be imagined as a single ...
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BoxTidwell and Interaction term sginifance vs plotting predictors against logit in logistic regression

I am running a logistic regression in R. After boxTidwell() I discoevered that the linearity assumption of logistic regression is violated. Decided to explore further with ploting the predictors ...
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Fixed effects - correcting for autocorrelation and heteroskedasticity, panel data analysis in R

I have a datset of 25 counties over 11 years, with response variable unemployment ( in %), and 6 explanatory variables (proportion with high school, some economic indicators, etc). After some tests ...
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How to check SEM assumptions?

This question is related to SEMs that include latent variables e those that not include in lavaan package. SEM assumes normality/multivariate normality, but it is being very difficult to found a way ...
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When does the boundedness of the dependent variable become problematic in linear regression?

Linear regression assumes that the dependent variable ranges from $-\infty$ to $\infty$. Many (most? all?) real DVs do not actually have such a range. For instance, the weight of adult male humans can'...
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How to check the assumption of homogeneity of variance visually using box-plots

Can anyone confirm if APA no longer recommends using statistical tests for checking assumptions? If so, what are the alternatives? I have been told to check visually but I am unsure how to check ...
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rmANOVA or mixed models when all assumptions are violated

I conducted a balanced 3x2x2 (Distance x Scale x Object) within subject design with 13 participants in my final analysis. The dependent variable is a continuous physiological measurement with about ...
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Statistical test to use to test mean equality given non-independence assumptions

In a survey conducted, 75 survey participants were asked to rate randomized keywords from groups 1-5. Every keyword belongs to a group and subjects were asked to rate each keyword. I would like to ...
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36 views

Application of logistic regerssion

Please, I have a question about the application of the logistic regression. If we measure the glycemia (blood glucose) among the same subjects group in three time (measures were operated in 3 ...
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1answer
42 views

Violating the assumptions of one sample t-test and wilcoxon's sign test

As far as the background of my research is concerned, I developed a framework for sustainability management in organizations through a systematic review of literature and sustainability reports. That ...
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How do I report a Friedman Test when the sample violates the assumption: 'Group is a random sample from the population'?

How do I report a Friedman Test when the sample violates the assumption: 'Group is a random sample from the population'? My study involves a group of participants receiving an intervention and a ...
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Functional data analysis references

I am working on a inferential framework for functional data. I have categorical independent variables and a functional response variables. Different implementations of functional linear models are ...
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weird assumption of one-way random effects ANOVA

$$Y_{ij} = μ \, +\, A_i \, +\,ε_{ij}$$ In Ch5 (random effects one-way ANOVA) of my textbook, it mentioned that $A_i$ (see the model above) is assumed to be $\sim N( 0, \text{constant_variance} )$ ...
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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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93 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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134 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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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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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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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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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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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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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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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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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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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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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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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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158 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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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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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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74 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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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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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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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, ...