Questions tagged [parametric]
The parametric tag has no usage guidance.
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Importance of normality testing in clinical trials / AB tests
I’m curious to read about the importance of normality testing in AB tests and clinical trials.
It seems that there is a lot of mixed (and strong) opinions about the necessity for normality testing, ...
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Importance of sample size for parametric tests [closed]
Why is sample size particularly important for parametric tests? This is my question.
These are the possible answers:
a.
Sample size needs to be bigger than 8
b.
Sample size needs to be large enough to ...
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Are there families of known parametric copulas for non-standard marginal normal distributions?
I know that a family of Gaussian copulas generates a standard bivariate normal distribution if and only if the marginal ones are standard normal. This characterizes the Gaussian copulas, where I have ...
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Interpreting hazard ratios in Royston-Parmar model (gammax, flexsurv::flexsurvspline)
I am a bit confused by the hazard ratios from the flexsurvspline model (Royston-Parmar). For a categorical variable (say X_1 with two levels, (a) and (b)) with time-varying coefficients, I can specify ...
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residuals in parametric survival analysis
This is probably a straight-forward question but I can't find a straight-forward answer. The topic is new to me.
I am performing parametric survival analysis, e.g. estimating a survival function from ...
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Example of a parametric test with no normality assumptions?
I read an article saying that "all parametric tests make an assumption of normality", which I know to be incorrect, since technically a parametric test could be done for any distribution, ...
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How do I sample new data for a parametric bootstrap with linear regression?
I initially have two data vectors $x$ and $y$, where $y$ is assumed to fit the linear model $y = \beta_0 + \beta_1x + \epsilon$, with $\epsilon \sim N(0,\sigma^2)$. I fit the model using fitlm in ...
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How to parameterize covariates in parametric time to event model (lognormal distribution)
I have a parametric time to event model for survival data and I found that a lognormal distribution has the lowest objective function value for a base model. Below is the hazard function for the ...
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Choosing the right statistical method - predictors for Knee function
I am new to statistics and I am struggling to choose the right statistical method for my work. I am trying to determine predictors for knee function after a specific type of knee surgery.
I have a ...
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If linear regression is parametric, do we need normality of the features and/or target? [duplicate]
From what I know, linear regression is a parametric model (as mentioned in here). Parametric tests requires normality of the variables. My first question is that this is an assumption of the linear ...
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Mapping Parametric Curves with auxiliary variables
The image below displays an approach of using an auxiliary variable to map the parametric curves of a standard normal pdf and cdf.
In Equation (1), z as r.v. is clearly one-dimensional. However, after ...
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Comparing before and after survey using Likert Scale
We are trying to measure if there is a difference on the level of interests of participants before and after I let them play a game. The survey is in the form of Likert Scale where ...
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Parametric or non-parametric if a variable is distributed normally and another non-normally distributed
I have 2 variables that I'd like to know if one (a concentration of a substance in a biological fluid) is dependent on the other (the percentage of inhibition of this fluid over the substance). I'd ...
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Use of both parametric and non-parametric tests in the same study
Suppose we are investigating whether there is a significant difference in dependent variables A and B between two treatments in a population. Let's assume that the data provide parametric assumptions (...
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Correlated linear survival model
I'm trying to model a survival situation like the following:
Say I have 100 data points, and each will survive some number of days before dying at some point. In my problem I know that over a span of ...
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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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Predicting time to event / duration data
I've built a parametric survival model (survreg in R) to predict injury recovery duration using features such as age and treatments. I'm looking at trying model-based boosting using mboost with ...
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Is Kernel-Regression parametric or non-parametric?
As the title says, is kernel regression a parametric or non-parametric method, and how can this be motivated/explained?
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Why are parametric models usually robust to mild misspecification?
Statisticians often use parametric families of models, for example normal distributions with unknown mean and variance. However, nothing in real life is perfectly normally distributed (or distributed ...
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Power calculation for two populations of equal variance
If I had a scientific assay which when run on a control population produces readouts which are normally distributed about the mean. A treatment which changes this mean does not change the variance of ...
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Independent Sample T-test or Mann-Whitney U test?
I am a very young stats learner, and I need help understanding the justification of a test choice. I have a sample of 39 participants (20 females and 19 males) been measured on task performance, and I ...
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Example of a parametric family of distributions that always has dependence on among its variables
Inspired by this question, I would like an example of a parametric family of distributions such that there is dependence for all choices of parameters. The family could be infinite or finite, but I ...
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Are there any parametric machine learnig models that can represent non-linear behaviour between a predictor and a targe variable?
Some basic models, like multiple linear regression (MLR), are parametric but usually limited to linear interactions between X and y. Other models can represent non-linear interactions between X and y, ...
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Why are parametric tests more powerful than non-parametric tests?
I'd like to understand why parametric tests are more powerful than their non-parametric alternatives. Is the word choice of "power" the same as statistical power? As I understand it, power ...
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Which test should I use to compare a normal distribution sample with skewed distribution sample?
I have two groups : Infection group (n=26) and healthy control group (n=127).
The aim is to see if there is a difference in the mean of T cells absolute count* values between the two groups.
Ho= the ...
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Survey sampling: How many participants per group (current, former, and potential users) should we recruit?
We are designing research in which we will explore the perception of users (C current, F former, and P potential) on a product. We apply the same questionnaire for each group adapting (verb tenses) ...
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What repeated measures statistical tests should I use with uneven sample size and parametrical/nonparametrical distribution?
I'm looking for a way to measure significance + variance homogeneity/heterogenity
First of all I tested my data for normality and it's not always parametrical, so I think that I should use different ...
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Data didn't pass normality testing for K-W and S-W but the skew and kurtosis were within range...advice please?
I am conducting a study on the relationship between rural/urban living, intentions and barriers to help seeking in adult males. I was planning to conduct a correlation and then pending that result, a ...
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Bias due to delayed entry?
Imagine I want to study career longevity of scientists. I define a career based on publication records. So a (publishing) career starts with the year of first publication and ends in the year of the ...
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When do we have nuisance parameters?
From Wikipedia:
a nuisance parameter is any parameter which is not of immediate interest but which must be accounted for in the analysis of those parameters which are of interest.
Suppose originally ...
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