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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2answers
34 views

General assumptions about functions in machine learning

In the article "A few useful things to know about machine learning" (ungated pdf), I found the following quote: In fact, the general assumptions, like smoothness, similar examples have similar ...
3
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2answers
126 views

Error term in linear regression

I'm reading about a linear model which is fit to an equation, $Y = \beta_0 + \beta_1X + \varepsilon$, where $B_0$ is the intercept, $B_1$ the slope, and $\varepsilon$ the error term. My question is, ...
10
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2answers
480 views

Why is the normality of residuals “barely important at all” for the purpose of estimating the regression line?

Gelman and Hill (2006) write on p46 that: The regression assumption that is generally least important is that the errors are normally distributed. In fact, for the purpose of estimating the ...
3
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1answer
98 views

Linear regression with violated assumptions

I am trying to find out the determinants of cognitive function. The outcome variable is the mini–mental state examination which is a 30 point questionnaire response that has score values from 0 to ...
4
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0answers
68 views

Repeated measures ANOVA: what is the normality assumption?

I am confused about the normality assumption in repeated measures ANOVA. Specifically, I am wondering what kind of normality exactly should be satisfied. In reading the literature and the answers on ...
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0answers
21 views

assumptions to compute mahalanobis distance

Which are the assumptions to compute the Mahalanobis distance between two groups? Do all the variables of the two groups be normal distributed?
0
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1answer
59 views

loglinear analysis, assumptions met?

We've data from a large ongoing project at a big science museum. We are showing people plates of food where we vary the plate shape (round or square; 0,1), food arrangement (polygonal or vertical ...
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2answers
171 views

Assumptions to derive OLS estimator

Can someone briefly explain for me, why each of the six assumptions is needed in order to compute the OLS estimator? I found only about multicollinearity—that if it exists we cannot invert (X'X) ...
0
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1answer
20 views

LogLogistic Survival Model Assumptions

I am working with Hospital Length of stay data for the first time. It is highly right skewed. In researching ways to approach this problem, I thought a survival model fits the problem description. ...
3
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2answers
40 views

Errors and Residuals

In Wikipedia , it is written that : the sum of the residuals within a random sample is necessarily zero, and thus the residuals are necessarily not independent. The statistical errors on the other ...
2
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0answers
19 views

Data Assumptions for AIC model comparisons

I recently started digging into statistical information criteria, more specifically the Akaike Information Criterion. As the literature I have read so far does not cover this, I was wondering whether ...
2
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0answers
29 views

IIA assumption: difference logit and probit

Considering the following question about the Independence of Irrelevant Alternatives assumption: Alternatives to multinomial logistic regression It seems as if IIA is only a problem when using a ...
2
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0answers
20 views

When to use Brown-Forsythe Test?

I have been researching the differences between Welch ANOVA and Brown-Forsythe Test. I know that Welch ANOVA is used for more than two groups comparing whether there is statistically meaningful ...
0
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1answer
31 views

Log transformation for logistic regression

Is it necessary to log transform non-normally distributed variables to perform logistic regression? If so, when is it appropriate?
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0answers
21 views

PH assumption: categorical variable (1 category does not interact with time)

After checking the PH assumption in STATA I found one variable (4 categories, 1=ref.) to interact with time (using 'tvc'). The 3th and 4th category had p-values <0.05. However, the 2nd category did ...
1
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1answer
45 views

Consequences of violating assumptions of nonlinear regression when comparing models and/or datasets

I have a question about the consequences of using non-linear regression when the data violate the assumptions of (1) homoscedasticity and (2) normal distribution. Specifically, I am wondering about ...
0
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0answers
12 views

What assumptions does Wherry's correction make about the k x variables yielding obs R?

I think it makes 2 important assumptions that are rarely if ever met, leading to adj. R that is almost always an overcorrection of obs R. If I'm right, I think I can offer a fix to both problems. I'm ...
0
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0answers
18 views

Wild bootstrap in “bordeline" case t-test

I have to compare the mean levels of a continuos variable y (ranging 1-20) subdividing my sample in two groups according to a dichotomous variables (i.e gender). Sample sizes of the two groups are ...
4
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1answer
62 views

Would you ever *not* check model assumptions?

I have encountered a statistician who is suggesting that for secondary analyses, she would not check model assumptions (e.g., linearity, normality). Sample sizes for each group are 26 and 28, and this ...
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0answers
23 views

Is Wild Bootstrap a good strategy in General Linear Model (ANCOVA) with Assumption Violations (both normal residuals and homoscedasticy)?

I need to perform several GLM's (i.e. ANCOVA’s, with a single continuos dependent variable and several predictors, one dichotomous and some other continuos). I was looking for both a significance on ...
0
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0answers
14 views

Is there another way to make pretest scores in a Solomon design match?

As a research design, I applied the Solomon design, resulting in four groups: no pretest - manipulation A - post test no pretest - manipulation B - post test pretest - manipulation A - post ...
1
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1answer
31 views

Linear regression confidence intervals variance assumption in practice

An assumption for linear regression confidence intervals is that the variance is the same for the dependent variable for whatever of the independent variable. If in practice the variance is ...
0
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0answers
28 views

Checking assumptions of a large sample - extremely confused

I'm working with a sample size of over 2000 and I have become extremely confused at the first hurdle... I plan to run three linear regressions and one logistic regression. If I was working with a ...
0
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0answers
49 views

glmer - testing assumptions

I've used lme for my data and the assumptions about constant variance, normality, and independent observations are violated, so I took that as an indicator than I have to use glmer instead. Now I want ...
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0answers
26 views

What is going on here? Omnibus repeated measures ANOVA is marginal, but follow-up planned pairs <.05

I have a repeated measure ANOVA with a decent sample size (124 participants, with a score for each person for 3 conditions). The data are moderate to strongly positively skewed, (though similarly). ...
0
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1answer
71 views

What test(s) should I use to compare 2, non-normally distributed populations with unequal variances? (IV is 2 categories; DV is ordinal)

I'm a bit stumped as to what test(s) is/are most appropriate for the following scenario. I found a couple of similar questions but wasn't sure if the answers applied. For a report I am working on for ...
5
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1answer
71 views

Question about normality assumption of t-test

For t-tests, according to most texts there's an assumption that the population data is normally distributed. I don't see why that is. Doesn't a t-test only require that the sampling distribution of ...
2
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1answer
56 views

Help with understanding the assumptions of Wilcoxon signed rank test

I am comparing the monthly losses for actual and forecast losses for the same time period to see if our forecasts are in line with actuals. This is for a 12 month period. I am bit confused about the ...
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0answers
19 views

Can the chi-squared be used to test monthly means for two time series?

Can chi-squared test be applied to compare two continuous random variables but where instead of counts we split samples into groups and into cells of the table we put means for groups? In our case we ...
2
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0answers
45 views

Departures from normality in factorial design

This paper (http://psycnet.apa.org/journals/med/6/4/147/) states that departures from normality can be tolerated for one-way ANOVA. "The results give strong support for the robustness of the ...
2
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0answers
11 views

References for visually inspecting underlying model assumptions

In connection to this popular question in CV, I was wondering which peer-reviewed papers / books could be used as references about using visual inspection of q-q plots etc. as compared to performing ...
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0answers
18 views

When can one use Hochberg's or Hommel's method for adjusting P values?

The p.adjust function in R can produce P value adjustments based on methods from Hochberg and Hommel, which are both more powerful than methods from Bonferroni and ...
3
votes
1answer
52 views

Is this a Random or Purposive Sample? Inclusion-Exclusion Criteria and the Sampling Frame

Introduction I am confused about when a sample is a random sample (i.e. probability sample) and when it is a purposive sample (i.e. non-probability sample). My understanding is that the former allows ...
2
votes
2answers
100 views

Can my Bayesian prior reflect what the data should say rather than what it could say?

Can my Bayesian prior reflect what the data should say rather than what it could say? For example, assume I collect data where $Y_i$ is whether or not student $i$ passed the test and $X_i$ is whether ...
2
votes
1answer
69 views

Power analysis on chi-squared test with low cell counts

I am hoping to perform a chi-square test of independence on data in a 2x2 contingency table with the following values: ...
0
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0answers
15 views

Is it necessary for covariates in an ANCOVA model to be normally distributed? [duplicate]

I am running an ANCOVA model and am trying to remain true to all the statistical assumptions. I noticed that one of my covariates is not normally distributed, I know that the X and Y variables should ...
1
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0answers
33 views

Does negative binomial regression assume sample independence?

I'm working with a negative binomial multiple regression and I'm wondering about the assumption of spatial independence of samples. White and Bennetts (1996) say that the assumption of spatial ...
0
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0answers
38 views

Nonlinearity in OLS-models

I have a question connected to the OLS-Model's assumption of Linearity between parameters. What should be done if the assumption is not fulfilled? My second question is if I can use multinomial ...
1
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0answers
55 views

Can I interact my randomly-assigned variable with another variable in TSLS?

I'm working on an IV setup that uses random courtroom assignment as an instrument for whether a defendant goes to jail or not. (Similar to here and others). I have about five years of courtroom data, ...
0
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0answers
28 views

Is Naive Bayes robust?

We know that according to Naive Bayes assumption input features are assumed to be independent of each others given the target variable $y$. Now, If we intentionally add a duplicate (exact copy of ...
4
votes
2answers
78 views

Can a one-way ANOVA be performed in these circumstances

I am supporting a psychology experiment, and having problems analyzing some of the data. By way of background, I’m a programmer at a research organization who’s taken several stat courses recently. ...
5
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2answers
177 views

Assumptions behind multinomial logistic regression

What are the proper assumptions behind multinomial logistic regression? And what are the best tests to satisfy these assumptions in any statistical software? What are other suitable models, if those ...
1
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0answers
102 views

Assumptions to be checked under Tobit model

Some researchers suggest that OLS assumptions must also be satisfied for other estimations (like Tobit, probit/logit, Heckman two-stage model). From the discussion here I understand that it makes no ...
2
votes
1answer
44 views

What is the nature of the normality assumption in models for longitudinal data?

I'm working on a longitudinal dataset to which I've been fitting non-linear mixed effects model in R. Regarding normality, I have a few questions: Can I assume that a longitudinal data is normally ...
0
votes
1answer
91 views

OLS assumptions

It is known that conducting post-estimation tests for OLS assumptions (Multicollinearity, heteroscedasticity, and endogeneity) is necessary. But is it statistically necessary to carry out these OLS ...
1
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0answers
81 views

Central limit theorem: applicability for assumptions of different tests

Since many statistical procedures (e.g. t-test, ANOVA, Pearson’s r (for efficient estimates)) require the normal distribution of the tested variables ('normality-assumption') one may ask if (at least) ...
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0answers
42 views

Is a model including a square root of a variable linear in the parameters? [duplicate]

Is the model $$ y = \gamma_0 + \gamma_1 + \sqrt x + \varepsilon $$ linear in parameters? ( $\varepsilon$ is the error term.)
3
votes
2answers
89 views

Is it an assumption of the normal linear model that explanatory variables are uncorrelated with the errors?

Some books seem to include an assumption for the normal linear model which I have never seen before. They say that there must be no correlation between between the explanatory variables and the ...
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0answers
16 views

Three percentage indicators into one (or two measures) in regression moder

I am working with a data set resembling the extract below: ...
4
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3answers
349 views

Violation of Gauss-Markov assumptions

Which of the Gauss-Markov assumptions is violated in this picture? If all other Gauss-Markov assumptions are satisfied, is the OLS estimator for $\beta_1$ unbiased and consistent? Why? In the ...