Questions tagged [small-sample]
Refers to statistical complications or problems due to having few data. If your question is about a small sample relative to the number of variables, please use the [underdetermined] tag instead.
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Hold-out Set -- Smallest Acceptable Size given somewhat rare event?
I am contemplating the appropriate percent train-test split (e.g. 90%-10%, 80%-20%)
Note I am asking about model evaluation, not cross validation/model building. This is for creating a hold out set to ...
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Paired t-test for 2 patients?
For my doctoral thesis work, I conducted a small feasibility study on the use of a virtual reality therapy protocol in preventing aggressive recidivism in 2 treatment-resistant schizophrenic patients.
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Correcting p-values when accounting for age and sex in a study where the main objective is to find differences between disease/control
So I analyzed my metabolomics data using Mann Whitney U tests and OPLS-DA. My data is super small, with the control group only having 5 samples and the other groups having 10 and 14 samples ...
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How to construct confidence interval out of a sample with small number of events?
I'm analyzing the results from an epidemiological study, where I have a sample of 2k persons with their respective ages and whether they were detected with a disease or not by different technologies. ...
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Questions regarding small-sample time series models
Thanks for your time handling my issues.
I have several time series models to be improved for the same data set.
Time series regression
The first model incorporates only 5 time stamps, whereas we ...
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What is the minimum number of data points/observations required to use Theil-Sen?
I am working on an algorithm which requires estimating trend magnitudes of data points. I have been told to use Theil-Sen as it is more robust to outliers and it is non-parametric. As users will be ...
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What do you think of this analysis for a small dataset with a weird experimental design?
I have a very small dataset (n<30) that is divided in 3 groups: healthy controls, patients with condition A, and patients with condition B. I am going to do a lipidomics analysis of the samples, so ...
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Proper analysis for vernal pool study data
I am trying to analyze a dataset consisting of counts of amphibian egg masses (3 different species) in nine vernal pools over a four-year period (consecutive years, 2014 to 2017). During each count (...
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What is the best hypothesis test method for a sample dataset with values less than 0.1?
I have a dataset with attributes X, Y, W, and Z. X is the predictor, Y is the outcome, Z is the confounder and W is the mediator. I have defined 1 STL formula for each attribute denoted by f(X), f(Y), ...
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Small sample sizes and transfer learning
I have a very small dataset (n = 18) of patients with certain key data as well as imaging. I have performed a clustering analysis (via PCA and hierarchical clustering) to cluster these patients based ...
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What does small optimism in predictor effect mean?
I'm reading the following paper by Burke et al.
Minimum sample size for developing a multivariable prediction model: Part I – Continuous outcomes
The paper discusses the minimum number of samples ...
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Do neural networks work with high-dimensional small sample data?
Are neural networks used for the classification of high-dimensional small sample data like gene microarray data, where the dimension may be on the order of 1000 features per sample with around 100 ...
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Resampling as prior distribution?
Suppose we've got a small dataset that we have no prior knowledge about and we're going to use linear regression on it. I have been wondering whether instead of fitting a normal OLS it would make ...
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How do you deal with a high Feature/Sample ratio?
I am working on a machine learning task with a small dataset of 130 samples, each with 66 features. When I try to fit a model to this data, I encounter issues with either overfitting or underfitting.
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Sample size Red flags for a data set I was asked to analyze, please help
I am working in polishing up work an undergraduate class did and the data set is raising a lot of red flags for me. Like to the point that if these concerns I have aren’t resolved by either redoing ...
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Do monthly sales of a retail shop have a unit-root?
Simple question to understand if by nature monthly sales from a retail shop on the high street are likely to have a unit-root in its timeseries or not?
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Strong difference between lambda.min and lambda.1se
I have run an elastic net on a relatively small sample (n= 320) with 17 predictors and 5-fold cross-validation (no train-test sample because of the small sample size) and 100 bootstraps.
When I look ...
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Sample size for prediction model
I am developing a prediction model for prognosis in 90 patients after an intervention. The result is almost 50% were recovered. However, this intervention consists of two different treatments. Since ...
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Is there some way to analyze nominal data with repeated measures when there is a very small sample size?
So I have some data of 16 patients who were subjected to a test a different number of times (some only once, some as many as 7 times). The response variable is definitely nominal (I wasn't involved in ...
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Unequally right-censored survival analysis
I'm trying to do a survival analysis and I want to know how to handle unequal right-censorship.
Essentially, people enter the trial at different ages and exit either at death or at the end of the ...
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Modeling continuous interaction effect with very small sample
I have a very small data set (n = 12) of high level athletes each with a set of measurements representing technique (5 variables) and a set of measurements representing strength (3 variables), and I ...
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small dataset for a regression task
I am trying to train a NN model in MATLAB to predict the amount of overflow for flooded junctions in an urban runoff system and I have 45 samples and 15 features. The issue is, I don't think 45 ...
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P-value adjustment for a single test with low sample size
I have a dataset of 2 conditions. Each condition has 15 measurements. I tested them using paired t-test to find if the difference is statistically significant. Should I use a p-value correction method ...
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Cross-validation as strategy for training
Let's say I have a classification model to be trained and a relatively small dataset. The data is splited in k-folds (eg. k=5), in such a way that:
A, B and C are used for training, D for testing and ...
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PLS model on wide dataset with 60 samples and 120 variables
Data health for PLS modeling
Hi,
I am working on a manufacturing data that is fairly new (only has 60 batches produced so far) dataset size is 60 observations of 150 variables and I am building a PLS ...
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Unsure of what analysis to use. Sample is too small for ANCOVA
I am trying to analyze some preliminary data for a conference. I currently have two animal participants completing a series of tasks.
The tasks use different types of feedback (4 levels), which vary ...
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Exploratory Analysis with Small Sample
I'm using data (secondary analysis) to conduct an exploratory analysis. I have a sample size of $n = 67$, and the exploratory analysis includes two independent variables and four dependent variables. ...
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Assessing the Validity of Conclusions Based on Limited Findings
Introduction: Archaeological research often involves drawing conclusions about past societies and cultures based on a limited number of artifacts or findings. In some cases, such as the study of ...
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Can you be 93,75% confident from a random sample of only five from a population of 10 000?
I recently read this passage from a website and I just can't work out the math.
Overall, it says you can be 93.75% confident of having the true median parameter within an interval, obtained from a ...
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Significance of a single point, or population of 1
This may sound simple but I'm lost. I have a simple experiment 15 controls and 15 treatments. 13 of the 15 controls were positive, but only one of the treatment samples was positive. This makes the SD ...
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Test of unique-ness [closed]
I have a sample of 20 drugs defined by about 30 parameters. I would like to run a "unique-ness" test to see whether one of the drugs is unique in any way relative to the other 19 parameters. ...
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Test if a single sample is likely to have come from the same distribution as a dataset
A certain experimental design foresees collecting 100 datapoints under condition A and exactly 1 datapoint under condition B. It may be assumed that in both cases the data is normally distributed. Is ...
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Alternatives to ANOVA to find differences between three groups?
So my data is looking at the incidence of emotions within therapy sessions. I am looking at three groups that I suspect have different pattern across several emotions
Group 1 n=36
Group 2 n=12
Group 3 ...
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Confidence interval for sum of independent but not identical bernoulli RVs with small sample size
I have a small sample size (5 <= N <= 10), and for each sample i, we observe independent $Y_{i}$ where $Y_{i}$ is the sum of 7 independent yes/no responses (i.e. bernoulli experiments), where ...
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Can variance be calculated with a sample size of n=1?
I am currently analysing inter-rater reliability/agreement data for a single case with multiple raters. For that I am using Gwet's $AC_2$ (as described here) using the irrCAC package in ...
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CFA with R - small sample size - also different outcomes at different times
I have the following problem:
We have a model of 3 latent variables with 8 observed variables each.
Our sample size is 19, which can't be upped because it is a special subgroup of the population and ...
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Is AUROC sample size-unbiased
Some metrics are sample size-biased, i.e., they will give biased estimates in small sample sizes. Is there a formal proof that AUROC is either sample size-biased or unbiased? I.e., will the ...
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Degrees of freedom for Two Stage Sampling when sample sizes are small
I am having difficulty to find information to determine the degrees of freedom (t-distribution) to produce a confidence interval for the estimated variance of the mean in a Two Stage Sample (SRSWOR) ...
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Small number of positives in a large dataset
I have a panel dataset with a very large number of observations 300,000. I am testing to see if a dummy variable is positive and significant using regular OLS. I have only about 1500 obs where the ...
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Ordinal logistic regression assumption
I aim to build for the first time an ordinal logistic regression between a dependent ordinal categorical variable (temperature sensation vote TSV, Y) coded on a bipolar ordered 6-point scale (from ...
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Confidence intervals for precision and recall of a small sample
I have a very small sample (N=12) of results from a classification problem, and would like to compute the confidence interval around the precision and recall. The results of the classification are (...
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Is it appropriate to use log-rank test in a study having multiple cases with expected values less than 5?
My goal is to show independency of factors related to survival of a small size sample (26 patients) for a period of time, this sample was divided in 2 groups (16 vs 10 patients), the events were ...
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Appropriateness of log-rank test [duplicate]
I'm working on factors related to survival of a small size sample (26 patients) for a period of time, this sample was divided in 2 groups (16 vs 10 patients), the events were little (7 in total). I ...
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To what what sample size does the CLT refer? The size of the random draw (the sample) or the repetitions in a (hypothetical) simulation? [duplicate]
Assume the following population:
If I draw many repeated random samples of size N from this population, their means should be distributed normally - according to the CLT. Here, I draw 100,000 samples ...
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Stability of results in non-inferiority test in small sample size with rare events
I am working with a dataset including 65 participants, 35 in the control group and 30 in the experimental group. The objective is to assess wether the experimental group is non-inferior to the control ...
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Splitting the dataset before GridsearchCV
I have a dataset of 390 rows. I have created a pipeline consisting of scaling, selecting features, and modelling.
I am using GridSearchCV (k=5) to find the optimal scaling method and to tune the ...
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Predicting end of month data from current data and potentially past data
I want to estimate the value of a quantity at the end of the month.
Currently, we use a very dumb method, which is simply to take the current rate at the current point in the month, get the rate (in ...
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Principal component analysis and Cronbach’s alpha
I have data from two Likert-items questionnaires, one administered to clients (n=31) and the other to professionals (n=8) . Most questions are identical or similar in the two questionnaires. The goal ...
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how to estimate the number of known words in a text
I would like to estimate the proportion of known words in a text from a sample of tested words, where a subject answers if they know the meaning or not, and the frequency of how often they appear in a ...
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Multiple regression with few observations and many variables
I have data about 40 stores described by 50+ continuous variables in terms of customer behaviour (types of purchases, demographic attributes, etc). I want to build a simple regression model to explain ...
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