Questions tagged [nonparametric]
Use this tag to ask about the nature of nonparametric or parametric methods, or the difference between the two. Nonparametric methods generally rely on few assumptions about the underlying distributions, whereas parametric methods make assumptions that allow data to be described by a small number of parameters.
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The hunt for a 'nice' flexible distribution [duplicate]
Background
Suppose I have data $\mathcal{D}_1, \cdots, \mathcal{D}_n$ with each $\mathcal{D}_i$ containing $m$ observations $X_{i1}, \cdots, X_{im}$; these observations are of unknown distribution, ...
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Strong consistency of kernel density estimator
I am studying the book Nonparametric and Semiparametric Models written by Wolfgang Hardle and have difficulty with the following exercise:
$\textbf{Exercise 3.13}$ Show that $\hat{f_h}^{(n)}(x) \...
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2
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How could Lilliefors use Monte Carlo if the estimand is not distribution-free?
Lilliefors test is a well-known statistical test for normality. Its idea is based on the Kolmogorov-Smirnov test, except the CDF is replaced by the CDF of the normal distribution with $\mu, \sigma^2$ ...
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How to construct homogeneous subsets table for nonparametric tests?
Does post-hoc for friedman tests or nonparametric testshave like a homogeneous subset table from SPSS? Mean doesn't represent it well so I tried using median but my data was zero-inflated so the most ...
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Parametric vs Non-parametric test recommendation
What type of non-parametric test would be suitable for the dataset shown in the image:
The sample size is 200 each for both variables. The data value can vary from 0-4 for both variables. The ...
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Is there a method bias when I prefer a specific post-hoc that shows a significance after significance in test of difference in groups?
I'm working to see if a machine does better than a worker in terms measurement (by having a measurement from an expert be the control). So my dataframe contains the Measurement Value, Measuring Device,...
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UMVUE of a parametric function [closed]
Assume $(X_1, . . . , X_n)$ is an i.i.d. sample from $P = \{f : f$ is a pdf and $E_f|X|< ∞\}$. Use the conditioning approach to find an UMVUE of $τ (f) =
(E_f (X))^2$.
Can someone provide a hint ...
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Why is histogram density estimation nonparametric?
My understanding of histogram density estimation:
For $k$ predefined equal-width bins $(b_0, b_1], (b_1, b_2], ..., (b_{k-1}, b_k]$ and $n$ observations $x_1,...,x_n \in (b_0,b_k]$, we estimate ...
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I have applied many statistical tests to my data, but still cannot determine normality
I have run multiple tests to determine normality on my dataset, but I am unsure which one to adhere to, especially since my histograms, density plots, and QQ plots leave much to be desired in terms of ...
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Multivariate analysis for non-normal variables
Edit: I am trying to produce a model in R in order to analyze the relationship between several variables. I am looking at the relationship between behaviour and dispersal of a population. Each ...
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If I have a very small n for one group and a very large number of features, should I choose a parametric or a non-parametric test?
I have a dataset that contains human metabolite concetration in a fluid. One group has about 12 samples, while another only has 5. My question is if I can assume normality for this data and do ANOVA/t-...
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Covariance between two binomial random variables or expectation of product of binomial random variables
I have an empirical distribution $S_n(x)$ (= proportion of samples less than equal to x) from a random sample $X_1, X_2, ..., X_n$ for a random variable $X \sim F_X$. Consider the random variable $T_n(...
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GLMM not working if I specify the distribution as gamma
Following is the histogram and Q-Q plot of deceleration data retrieved from driving simulator experiment. As the data is not normally distributed, I am using generalized linear mixed model to analyze ...
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Non-Parametric Test for Regression Significance
I have created a plot of the regression slope of sea surface temperatures (x) and an atmospheric variable (y). Although, I need to test the statistical significance of these trends using a non-...
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Comparing data with opposite distributions
What test can I use to compare whether the difference between the following sets of data are significant.
I know, I can just look at them, but I'd like it to be a bit more scientific than that. The ...
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How to determine significance for a Corrado rank test in an event study?
I apologise if this is a stupid question (it feels stupid tbh). I am currently doing an event study and my abnormal returns are not normally distributed. I am now in the process of performing a ...
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Mixture of Conditional Random Variables by Sampling
I am struggling to put my transformation of data into mathematical contexts. My goal is to define a mapping that transforms the original data into some awkwardly mixed data. In my simulation study, I ...
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Is this nonparametric tests with the same data valid?
I have 6 algorithms, and each algorithm I use on N problem instances (say N is around 200).
I divided the algos into two groups, 3 into group A and 3 into group B. They are divided into two groups ...
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Understanding the bootstrapped method for calculating non-parametric p-values
I'm trying to understand the non-parametric bootstrapping to calculate p-values. I understand pearson correlation has it's own method for calculating p-values but I'm just using this as an example.
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Anova violates normality assumption for error data
I have a 2 x 2 repeated measures ANOVA (N = 51) with Error Rate data as the dependent measure. The error data violates the normality assumption, even when outliers are removed. I have looked at the ...
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Alternative to Bonferroni Correction for Dichotomous Variable? [closed]
I am working with a dichotomous variable and my supervisor has asked me to apply a Bonferroni correction to our data using SPSS. From my understanding, Bonferroni corrections are used when performing ...
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Appropriate tests and normalization approaches for highly non-normal data
I'm trying to ascertain whether a particular type of article, $T$, is associated with higher engagement scores in academic journals, and how substantial the effect size might be. I have raw data of ...
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Multiple regression on unpaired data (A~B+C)
I am not sure how to test one of my hypothesis from my data.
Basically, I have 3 behavioral measures A, B and C, and I want to test that A is a composite of B and C: A = B+C
However, for practical ...
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OLR for non-normal continuous dependent variable with two categorical independent variables?
ID
Sex
Surface
B1
1
female
UN
1255
2
female
UN
542
3
female
UN
818
1
female
UN
274
2
female
UN
261
3
female
UN
314
1
female
UP
552
2
female
UP
548
3
female
UP
721
1
female
UP
431
2
female
...
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Projection pursuit regression
Projection pursuit regression (PPR) is described in Hastie et al.'s The Elements of Statistical Learning in the chapter on neural networks. The algorithm was introduced by Friedman and Stuetzle (1981)....
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How do I compare my data with the general population data in SPSS
My purpose is to compare my data with the general population data derived from a published report. I can only extract mean, median, 5th, 95th and 97.5th percentiles from it. Also, My data is non-...
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Regression models that conform to functional groupings of features
For example, suppose we want to predict y with features x1, x2, x3, x4. If I specify
...
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Can ANOVA suffice for comparing mean of percent/proportion data?
I've been handed off some data to analyze and I'm looking for something simple and straightforward. The 1 response variable/dependent variable is average percent mortality from 7 treatment groups (...
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Dunn test in R: comparison between levels of a single factor in a 2-factor experiment
For a 2-factor experiment, the TukeyHSD function in R (after a significant ANOVA) can calculate P values for the differences between levels of a single factor (basically, comparisons between the ...
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Bonferroni correction gives weird results in R
I have this dataset:
Treatment
data
T1
0
T1
0
T1
0
T10
0
T10
0
T10
0
T11
0.2
T11
0.2
T11
0.2
T12
0
T12
0
T12
0
T2
0.7
T2
0.6
T2
0.6
T3
0.8
T3
0.7
T3
0.8
T4
0.3
T4
0.3
T4
0.4
T5
...
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Gaussian white noise model in application
I am interested in applications (to data) of non-parametric statistics, and my question concerned the Gaussian white noise model defined by,
$$
X_{t_1, \ldots, t_d}=f\left(t_1, \ldots, t_d\right) d ...
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In an A/B test, how can you check if assignment to the various buckets was truly random?
Trying to figure out how I can confirm that my A/B Test assignment is truly random. I know the runs test is used to test for randomness.
Is it possible to use the runs test to check if my A/B Test ...
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Non-parametric test for comparing means of 2 or more dependent variables in R?
I have a matched paired dataset (student survey before a topic was taught and student survey after the same topic was taught) where I compare the means of their answers (answers are given in Likert ...
denise
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What exactly does the “symmetric distribution” assumption of the Wilcoxon signed-rank test refer to? [duplicate]
I have two lists (or sets) of data that I would like to statistically compare. More precisely, I would like to check if the difference between data list one and data list two is statistically ...
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Relation between the sample size with the powers of Kolmogorov Smirnov, Cramer Von Mises and Anderson Darling?
I want to know the mathematical relation between the sample size with the powers of 1. Kolmogorov Smirnov, 2. Cramer Von Mises, and 3. Anderson Darling.
I have seen many posts and other websites ...
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Estimation of Propensity Score using Random Forests
Suppose that one has a binary treatment $Z$, and assume that $Z=1|X=x \sim Bern\left(e(x)\right)$.
Furthermore, suppose I want to estimate the propensity score by a random forest. Are there ...
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Statistical power and sample size determination using Kruskal-Wallis test
I have data that represents treatments applied to a given number of subjects in two or more groups. After each treatment, the subjects in each group are appraised to be of quality 1-5 and the number ...
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Kruskal-Wallis as a non-parametric alternative to 2-way ANOVA?
I'm a master student currently working with taxonomy and cultivation of wild edible mushrooms. In my experiment, I'm evaluating the effect of 4 distinct solid culture media and 4 temperatures on the ...
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How to deal with negative values after subtracting the background?
I am working with Luminex data and have a question regarding the treatment of negative values after subtracting the background average. Specifically, I would like to know if these negative values need ...
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Statistical test for differences where output is -1, 0, 1?
He's the situation, say we have n data points. There are two treatments A and B. If treatment A was better than treatment B we give a score of 1, in the opposite case we give a -1, and if there is ...
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Central tendency to present in table in relation to hypothesis test
I am doing hypothesis test on the data to compare group A and B and there are multiple variables that I tested.
Due to the distribution of some of these variables is skewed and there are some extreme ...
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How to compare more than two groups of continuous, not-normally distributed values?
I'm currently analyzing the age variable in a dataset of all italian phyisicians (~470,000 obs) and I'm trying to check if age is significantly different between three groups defined by another ...
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Calculation of a nonparametric equal-tailed (central) tolerance interval for an unknown continuous distribution
Assume we have a sample of size $n$ from an unspecified continuous distribution $F(\cdot)$. We wish to construct a tolerance interval to contain $(100\,\beta)\%$ of the population with a pre-specified ...
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Comparing non-normal data between three groups
I am analyzing a dataset, where I have 3 categories (independent variable), and one continuous value (dependent variable). I am studying if the continuous value is significantly different between the ...
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How to measure reproducibility for repeated measures
I have run an experiment where in a series of trials, each of 10 animals was presented with each of 6 stimuli, and each stimulus was offered once to the left and once to the right nostril. Overall, ...
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Lower bounds for non-parametric regression in sup-norm with bounded noise
It is well-known that lower bounds on the nonparametric regression convergence rates under Gaussian (and more general unbounded) noise assumptions are given by $n^{-\frac{\beta}{2\beta + d}}$ in the $...
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2
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Distribution and variable analysis
I am doing a statistical test (program used is SPSS). On the basis of distribution and sample size, I have to chose the correct variable analysis. I also have to justify every decision. I have two ...
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Non-parametric test with two independent variables
My dependent variable is a raw score at some test that has a likert scale (ordinal data). My two independent variables are sex (male or female) and amyloid status (AB+ or AB-). I want to test the main ...
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34
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Assessing the Impact of a Specific Treatment on Survey Results: A Wilcoxon Signed-Rank Test Approach on Paired Samples
I have conducted a survey with several scale questions ranked 1-10 on a sample of n=18. I applied a specific treatment before and after the survey. However, I'm unsure about how to analyze the data ...
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2
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Seeking suggestions for a non-parametric version of two-way ANOVA/multi-variable MANOVA with repeated measures
I've been reading around this and keep coming up short so I'm hopeful there's an easy test for this.
I am measuring the differences (on a Likert scale) between matched (paired) pre- and post-lesson ...
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