Refers to any statistical complication or problem due to having few data.

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0answers
11 views

Few-clusters bias correction for cluster robust covariance matrix in random effects model

I'm currently working on some experimental data. Subjects are randomly assigned to one of two treatments. For each treatment I ran three sessions with 20 subjects each. In each session, participants ...
2
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1answer
12 views

Cross validation and small samples

I have a sample of 415 observations. With a sample with this size, it's possible to use cross validation?
0
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0answers
35 views

Is my sample suitable for elastic net? What are the assumptions?

I was hoping to use multiple regression to identify significant predictors but I have a tiny sample size (group 1 n=9, group 2 n=37) so I'll be unable to do this. I have read that regularisation ...
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0answers
4 views

Model Specification tips for increasing the power of a GLM model with small sample size? (SAS)

I am working on a model that uses a wide variety of categorical predictors vs. a continuous dependent variable. Unfortunately, my usable n ends up being 28. I am having difficulty getting significance ...
2
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1answer
73 views

Regression with very small sample size

I want to run a regression with 4 to 5 explanatory variables, but I have only 15 observations. Not being able to assume these variables are normally distributed, is there a non-parametric or any other ...
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2answers
40 views

If one group has 23 participants and the second group has 117 participants in it, can we rely on the result of t-test? [duplicate]

I was evaluating a research paper in which the authors have 23 male participants and 117 female participants. They have applied t-test to calculate Gender differences and have even concluded on ...
1
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1answer
17 views

Increasing statistical power by having a highly sensitive outcome measure

Is it logical to say that you can increase statistical power by having a highly sensitive outcome measure? I say this because a highly sensitive test has low Type II error, and low Type II error leads ...
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0answers
13 views

Poisson confidence interval that accounts for time?

I've gathered Poisson-distributed data and would like to compute a confidence interval, but the number of events and the amount of time are very small. Since standard CIs for rates aren't appropriate ...
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0answers
34 views

Rule of Thumb for minimum length of time series for Autocorrection estimation

I had a related question answered here: Rule of Thumb for minimum length of time series for AR(1) estimation However the answer gives rise to a new question. I want to be able to estimate the Auto ...
2
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1answer
42 views

Rule of Thumb for minimum length of time series for AR(1) estimation

I have a data set of 350 points, I want to estimate the lag 1 auto correlation for different sub-sets of the data. More precisely I want to take non overlapping windows of length 1,2,3....n and ...
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0answers
16 views

regression analysis for dataset with few predictors and few samples

I have a small pilot dataset containing experimental measurements for 12 samples, 4 numeric predictors and 1 numeric outcome variable. The goal is to obtain a first rough estimate on the extent to ...
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0answers
44 views

Validating Bootstrapped Probability of Survival Results From Small Sample Size Data

Quite often in industry, due to cost and schedule constraints, decisions must be made on small sample size data. I have 4 cycles-to-failure values resulting from running samples to failure in a ...
1
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1answer
45 views

parametric bootstrap for low sample sizes

I believe that this question is sufficiently different from previous related ones to warrant a new post. (I apologize if it has been answered already) I need to decide between various resampling ...
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0answers
17 views

How to equalize lower accuracy on larger sample sets?

I have a collection of image samples that I want to OCR. I also have the ground truth of the text on these images. Now I OCR them and eg. 10 of 100 samples are wrong. So I got an accuracy of 90%. ...
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0answers
10 views

What are some suggestions for analysis of and model development for a small sample of data?

I originally planned on path analysis utilizing multivariate multiple regression to test my hypothetical model - but I am not getting my sample size. I have looked at non-parametric regression ...
1
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1answer
33 views

Compare two small groups (population vs sample) over time

I am studying banks behaviour according to 6 financial rations throughout a 3-years period. I have 32 observations separated into two groups: large (6) and medium-sized banks (26). However, since in ...
26
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4answers
679 views

Can bootstrap be seen as a “cure” for the small sample size?

This question has been triggered by something I read in this graduate-level statistics textbook and also (independently) heard during this presentation at a statistical seminar. In both cases, the ...
8
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2answers
204 views

Bootstrap: the issue of overfitting

Suppose one performs the so-called non-parametric bootstrap by drawing $B$ samples of size $n$ each from the original $n$ observations with replacement. I believe this procedure is equivalent to ...
1
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1answer
97 views

small sample size, large number of variables (most categorical) - how to proceed?

I would be grateful for general guidance/advice about data analysis with some data that is problematic for me because of the small sample size, and the large number of categorical data. I realize this ...
1
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2answers
76 views

Given a series of past coin tosses from an unfair coin, how can I calculate the confidence for the next toss result?

So this is really difficult for me, but I would like to know if this is possible. Let's assume I have an unfair coin (absolutely no assumptions can be made about the coin), and my past result has ...
2
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3answers
284 views

Pattern mining on a small data set

I have a small data set 30 features/predictors and 30 observations. My target variable is Oil production and my predictors are well & reservoir properties (depth, trajectory, temperature, pressure ...
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0answers
7 views

Modification of categorical outcomes in small samples

I have a set of abnormal lab findings and a set of tenderness outcomes in a small sample of "cases" and "positive controls". We hypothesize there may be some lab findings which differentially affect ...
1
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1answer
61 views

Should a Poisson regression be carried out with only 3 data points?

I'm trying to test the relationship between the number of adults counted and the percentage heather cover over 3 areas. The data looks like this: ...
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0answers
47 views

What are appropriate validation methods for a Bayesian network model with low sample size?

I am currently using a Bayesian network model with 20 variables and 210 data points, with 15 locations measured at 14 different time points each. There are also some restrictions on what types of ...
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0answers
8 views

What are some guidelines for sample size when constructing a Bayesian Network?

Both general advice and advice specific to my case below is welcome. I'm trying to contruct a Bayesian network with 20-30 continuous variables. I have 15 locations sampled, with 14 time points each. ...
1
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1answer
23 views

Which non-parametric test should I run on ordinal data from a small sample?

I have one group of six raters who scored recordings of two separate six-person groups of participants, each group under separate conditions. While the participants were divided into two independent ...
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0answers
10 views

What test to use when analysing methylation differences with very small sample size?

I have not been capable of figuring out which test to use for my data, so I hope you can guide me in the right direction. I have array DNA methylation data for 5 families. From each family I have ...
3
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1answer
81 views

OLS regression - robust estimates for parameter's variance

I'm estimating a model for corporate social responsibility (not important). I have found my variable of interest significant at 5% confidence level. My sample is $N=84$, cross-section. For this I ...
0
votes
1answer
52 views

What are appropriate tests for goodness of fit on glm with a small sample size?

I've thought quite a lot on large sample size inference where the strong law of large numbers is easily validated. In my case however, I'm trying to infer the sign and magnitude of an outcome where ...
1
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0answers
30 views

Random sampling the data again to keep equal size across groups

I have an experiment with a between-group variable. It has 3 groups in total. When conducting the experiment, although we did random assignment for participants, the size of the 3 groups end up ...
6
votes
2answers
263 views

Is the sampling distribution for small samples of a normal population normal or t distributed? [closed]

If I know that the population is normally distributed, and then take small samples from this population, is it more correct to claim that the sampling distribution is normal or instead follows the t ...
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2answers
99 views

How to choose predictors for regression model

I want to predict reaction times using several personality scores. I have 9 different personality scores. My sample consists of 23 participants. Aren't there too many predictors if I put all 9 in one ...
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0answers
29 views

Best estimator for small samples

I have a sample of an unknown distribution for which I would like an estimate of the true value and the expected error on that estimator. Since the underlying distribution is not necessarily Gaussian ...
1
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1answer
57 views

For a T-test, what would happen if one of my samples was made up of only one observation? [duplicate]

I must be missing something, or under-thinking what goes on with a basic T Test, but I was under the impression that if I do a T-test, and one of my samples was made up of only one observation, the ...
2
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1answer
59 views

Small sample, many observations. Is the sample large enough?

I am working on a project regarding the influence of temperature and other variables on the sales of 3 branches of one local bakery. The research goal is to be able to better predict bakery sales (in ...
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0answers
16 views

How to create a weekly alert system that works for different sample sizes?

I'm trying to build a weekly alert system to let me know when something unusual has happened in my analytics data that might require further investigation. Currently there is an outdated system in ...
3
votes
1answer
55 views

Can Poisson regression be run with a small sample?

I am just a beginner. I have a sample of 71. I wish to do a Poisson regression. Is this sufficient for estimating a Poisson model? Should I use only counts as $Y$ variable or should I use percentages ...
1
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0answers
15 views

Methods for analysing effects of percentage mortality on population data with zero/low abundances

I want to analyse the effects of percentage mortality from two sources (a predator and a disease) on the population abundance of a host measured at 12 sites for 8 years, with the main aim being to ...
1
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1answer
94 views

How to model a skewed Student's t disribution

I have a small number of samples (5) of a large population (~10,000). The samples are percentages and hence I know from the context that no answers are possible below 0% or above 100%. From this one ...
2
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0answers
48 views

How can I tell if I my sample size is large enough for reliable feature selection using LASSO regression?

I have a gene expression dataset with 20 samples, and am not going to be getting any more. There are ~28,000 genes and four clinical covariates associated with each sample. The gene expression values ...
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0answers
48 views

repeated measures design between subjects with non normal and small N

I’m examining the effects of a parent-delivered reading intervention on 11 child outcome variables at 3 different time points (pre, post-intervention and follow-up) with a control group. Total sample ...
3
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0answers
75 views

Big Data? Have we solved Small Data yet? [closed]

There has been a lot of attention on Big Data recently, where the problems are often more logistical (how to deal with large volumes of data) rather than statistical. At the other end of the spectrum ...
1
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1answer
35 views

How to expand sample subset with similar data

I would like to categorize a large sample and make some estimates for each category aka subset. The problem is that some subsets contain very few data points. How do I deal with that? For example: ...
1
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0answers
104 views

Why are small sample sized avoided in meta-analyses?

In most meta-analyses that I've read, the authors choose to exclude studies with really small sample sizes (e.g n=10). Why is that? Speculation I could speculate that one reason is that since the ...
1
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1answer
209 views

Suggest models for prediction based on small sample data

I am not a traditional statistics guy. I am from an electrical engineering background. So, spare me for lack of jargon. The model is to be used for predicting agricultural output based on previous ...
2
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2answers
74 views

Comparing different conditions on a binomial distribution

I have some data where I have tested a binomial random variable under 4 conditions. The null hypothesis is that they all have equal means, alternative hypothesis is that one or more means differ from ...
2
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1answer
41 views

What test of significance is best suited to compare concentrations, with only one sample of each population?

I have two large reservoirs of water with unknown concentrations of bacteria. I have only one sample of each reservoir: Sample of reservoir A: volume of the sample $=V_1$, number of bacteria in the ...
1
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1answer
37 views

(very basic) One-sample test for binary data

I've repeatedly measured a continuous variable and each measure has been assigned a populational percentile range it falls into (percentile ranges were estimated for general population in another ...
4
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3answers
318 views

Regression for really small data with high degree of multicollinearity and outliers

I'm working on a promotional response analysis. I have a really small real world dataset with 25 observations and 15 variables. The variables have a high degree of multicollinearity and some have ...
0
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1answer
90 views

Testing difference between two means. Skewed ( N1=21) vs Symmetric bell (N2=47). Wilcoxon rank sum test appropriate?

I need to test to compare the means of two samples, one with size 21 and the other with size 47. Histograms show Sample 1 is skewed to the right while Sample 2 has a bell symmetrical shape. ...