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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How to design cross-validation and testing scheme when N is small?

I have a binary classification problem with 60 samples (N=60). 40 are responders (+) and 20 are non-responders (-) to a drug. There will be ~20 measured features (p=20) per sample with which to make ...
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Combine multiple small data as one to create a time series model

I'm an intern working on a project to forecast multiple products. Each product has small dataset, < 30, and I used ARIMA, SARIMAX, and other simple methods to create models but they didn't provide ...
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Getting trustworthy results from small samples and small population

I am an undergraduate student of psychology from Indonesia. Right now I am doing a mini research project where I correlate geographical data to outcomes at the provincial level. The hypotheses is that ...
1 vote
1 answer
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What are the minimal sample size requirements for cross-validation or bootstrapping?

I hope it makes sense to even ask these questions, but I'm wondering how can I evaluate the "validation" procedures that my data allow me to perform (i.e. cross-validation or bootstrap: ...
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1 answer
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Predictive modelling strategy for spatial interpolation: complex data structure, small sample size, but n > p

I apologise in advance for the long post, my questions are deeply interconnected so it felt wrong posting them as separate threads. Please note also that I edited this post to account for Florian ...
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10 votes
3 answers
800 views

Studies with small sample sizes

I'm asking myself the question of why studies with small sample sizes are not as convincing as those with larger sample sizes, and when this becomes a statistical issue. A complaint I've heard a lot ...
2 votes
2 answers
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Which confidence interval can I use to a report on a small survey?

Suppose that I made a survey with multiples questions where I have a target population of size nearly $N=100$ and a sample of size $n=8$. Is it possible to create any type of confidence interval for ...
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Analysis of a continuous outcome for a treatment in a very small sample size (6 treatment, 5 controls) while adjusting for confounding variables

I have to assess changes in a continuous outcome after a treatment, however, my sample size is very small (6 treatment, 5 controls). Also, I need to adjust for 4-5 confounding variables such as age, ...
1 vote
0 answers
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How to determine if a given sample size is appropriate for Betti number estimation?

A popular approach in topological data analysis is persistent homology (Chazal and Michel 2021 for an intro), but it is not clear to me what sample sizes are appropriate. Some talks seem to use ...
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Transfer learning with logistic regression and additional features

I have a logistic regression model's weights developed from another dataset. I also have a dataset with much fewer sample for one class, so the performance of the models developed on this dataset is ...
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Effectively evaluate a model with highly imbalanced and limited dataset

(This question was originally posted on the Data Science stack.) Motivation Most data imbalance questions on this stack have been asking How to learn a better model, but I tend to think one other ...
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Statistical method for small data in percentage

I have 5 measurements for 2 groups, and this measurements are in percentages. I want to compare if the percentage of Group A is different from the percentage of Group B. I thought about Mann-Whitney ...
6 votes
2 answers
241 views

Paired, discrete hypothesis testing

I am facing the following situation. I asked my class of 19 students to rate their interest about a certain topic on a 1-5 (discrete) scale. I then spent some time teaching them about this topic for a ...
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1 vote
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Nested Cross-Validation with Small dataset

I am currently working with a small dataset (only 175 samples, 45 features) and have been reading on the proper way to cross-validate my model. I had started with a basic cross-validation using a grid ...
2 votes
1 answer
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CLT for t-test with unequal sample size; one group < 30?

CrossValidated has many discussions on how unequal variances are not a practical issue for two-sample t-tests when Welch correction is used and on how normality assumptions do not play a role (in Type-...
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1 vote
1 answer
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Dealing with very small and unbalanced data

I am working on some TV series data, so the number of records is very limited. I have 58 instances, one for each existing episode, which I have randomly split in 45 and 13. The main goal is to make a ...
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2 votes
1 answer
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Is winsorizing limited to the usage of a certain percentile cutoff?

The Context My dataset consists of 68 groups, each with 4 data points inside it. As means of a robustness test, I am looking to see how the type of average/mean I use impacts the analysis that I will ...
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9 votes
1 answer
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What are "poor finite sample properties"?

In MacKinlay’s (1997) well-known article about event study methodologies, he states that there are two ways event clustering can be accommodated in event studies. Event clustering means that event ...
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1 vote
1 answer
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Can a slightly overfitted model be useful for exploratory (i.e. hypotheses generating) modelling?

Let's say you have a set of potential explanatory variables (e.g. p = 8) that you think are important to explain your response variable ($Y$) but your sample is too small to include them all in the ...
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1 vote
1 answer
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Is it possible to compare means of pre & post intervention questionnaire for only 3 participants?

I am completing my dissertation which was to determine if a 6-week expressive writing intervention would reduce aggressive behaviors & increase emotion regulation in students. My first variable (...
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0 answers
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Small n - dimension reduction and regression

I am trying to develop a valid method for modeling some biological data. I do not need it to be predictive necessarily, but I want to be able to show relationships and determine which set (of many) ...
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25 views

Can we perform ordinal regression on n<30 using bootstrapping?

The data collected aims to analyze an institute's performance and they have an only a small number of employees working, I want to establish a model using ordinal regression can it be possible?
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1 vote
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Will multiple regression work in my small sample?

I have a sample of size n=14, with 1 dependent and 6 independent variables (iv). r=0.85 with the first iv, others are 0.4 or less. Will multiple regression work? If not, why not? All I have is a ...
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Exact Logistic Regression with Dummy coding for predictor

I've been struggling to find a way to analyze my data. I have group number (group 1~4) as a predictor and a single dependent variable (A or B). Group 1 is "control" or "baseline" ...
1 vote
0 answers
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For small sample sizes, is jackknife superior at controlling Type-I error compared to bootstrap?

This question is motivated by the post here: Can bootstrap be seen as a "cure" for the small sample size? In the referenced post, we see that the bootstrap approach does not control type-1 ...
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What methods can I used to assign cases to groups when some variables are dependant on others?

I have a sample size of 42 cases, with about 5 variables for each case. Most of these variables are measurements, and I want to assign the cases into 2 groups (condition present, and condition absent) ...
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2 votes
1 answer
122 views

Kruskal-Wallis test on data with heterogeneous variance and small sample sizes per group

I've been trying to figure out how to test (in R) if there are significant differences between the group means of my data because it seems to violate the assumptions of tests that do this (ANOVA, ...
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Modification of Outliers

I have a practical / applied statistics question. I'm dealing with a specialized dataset with a very small sample (i.e. n < 10). In the sequence of observations, it is possible that a new ...
3 votes
0 answers
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How to deal with very little data

I thought I understood the train/validation split basics but this question got me confused. I could acquire very little data. I don't have it already, which is why I cannot just experiment with it. I ...
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1 vote
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Using Cramér's V to evaluate correlation between categorial variables with small numbers within contingency tables

I am evaluating correlations between categorical variables in a data set. I have seen Cramér's V is one way I can calculate this, and I know it takes the chi-squared statistic as one of the elements ...
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0 votes
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28 views

special form of a paired design (very small, unbalaned)

I am trying to figure out how to analyze following design. Suppose three samples are taken from the starting material of an experiment which will be performed at larger scale (LS). The same ...
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6 votes
3 answers
131 views

Should stepwise regressions also be avoided for exploratory (hypothesis generating) modelling?

In a recent paper, Andrew Tredennick and colleagues (2021) suggested to use the drop1() function in R for exploratory modelling (that is to generate new hypotheses ...
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SMALL SAMPLE SIZE: Can i use it for a validation study? What evidence supports this?

I would like to validate submaximal exercise tests; I will correlate the predicted maximum oxygen consumption values using the field tests (values will be derived from standard equation) with the ...
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1 vote
0 answers
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How to correct for unequal sample size per group in neg. binomial regression

My data contains information on the time, location, and present conditions of a fish catch. The problem we often have in the field is that not all locations can be consistently visited every time. ...
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1 vote
1 answer
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one-sample t-test on zero variance sample

I have to compare many gene-expression values between a group of 3 patients and a control patient. I choose to apply the one sample t-test (ttest_1samp from python <...
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0 answers
57 views

Wide prediction intervals for short time series: how to fix that?

I have very small time series data(24 points) for sales for different-different regions. I need to build Range Forecast (Confidence/Credible Intervals) for sales around it for every region. I tried FB'...
0 votes
1 answer
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What statistical test of significance should I use when comparing two small, unequal groups of non-normal distribution?

I am trying to analyze quantitative data between two independent groups. One group has 8 data points, and the other has 9. I used a Shapiro-Wilk test for each of the groups to determine normality, and ...
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0 votes
3 answers
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How to handle generate more data in small data-sets for regression?

I have a logistic regression and decision tree classifiation model with a dataset with 70 data entries, yet only 16 responses have said yes for the response variable. I have 8 covariates. How can i ...
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0 votes
0 answers
60 views

How to find an optimal sample size (or range) based on sampling errors?

Intro to problem Increasing the sample size can be very costly in terms of time and money. However, in experiments where we measure proportions within a sample, errors associated with the sample size ...
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0 votes
1 answer
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Why is hinge loss suitable for small training data sets?

In this blog post it says "Hinge loss is one such example which makes training with small dataset possible." Why does that hold true? So far, I could not come up with a convincing ...
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0 votes
0 answers
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Small N analysis for a field experiment question, and rare events logit

so, I am running a "Field" experiment, meaning, people in a real life situation are subject to certain treatment, and I am trying to measure the effect of said treatment. In this case its an ...
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0 votes
0 answers
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Do poisson regression and exact poisson regression only differ in confidence interval?

The point estimates from the two approaches are the same, right? I plan to use exact Poisson regression for a study, since the events could be sparse after adjusting for a few covariates. Is there ...
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0 votes
0 answers
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Final model training after cross validation for a regularized neural network

I have a regression problem with a relatively small number of available samples. In order to select the best model and tune the hyperparameters, I am using nested cross-validation (NCV). The common ...
1 vote
0 answers
17 views

Formula for Leemis's m

I'm looking for the formula to calculate the statistics and the significance level of Leemis's m. Wikipedia reports the statistics as $$m = \sqrt{N}\cdot\max_{i=1}^9 \left\{ \left|\Pr (X \text{ has ...
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3 votes
1 answer
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What's the correct tool to compare means between very small groups?

I'm not really used to VERY small samples, so I'm wondering what to do in the following situation: I have 3 groups, A, B and C. Each of them consists of 3 observations. I want to test whether there is ...
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Small Sample - Confidence Interval Mean

I have a sample size of 14 and I plan to measure confidence intervals for the mean of different characteristics. I can say this about my data: ...
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0 votes
0 answers
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Using dimensionality reduction to control for more variables in a multiple linear regression without breaking the 15:1 rule - possible?

I'm interested in whether there is a relationship between my particular variable of interest (X) and my dependent variable (Y). I'm planning to explore this using multiple linear regression. My focus ...
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0 votes
0 answers
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Estimate minimum sample size for a rolling time-serie percentage

I have to calculate the conversion rate for a web page, defined as CVR = orders / clicks This is an e-commerce web page, so clicks arrives to the web page ...
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0 answers
9 views

How can survey data for a small sample be analysed?

A survey was conducted among companies regarding the prevailance of a technological device in their company. It collected categorical data and received 40 responses (from a population of 520). As the ...
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What is the degree of cell sparsity that Poisson model can tolerate?

For models with no interaction terms, my understanding is that all the marginal cells need to have non-zero counts, in order to have finite estimates. If this minimum requirement is satisfied, will a ...
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