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

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Comparing change in lateral root densities between treatments for different genotypes

I have been growing 4 genotypes of the same plant and been recording their lateral root density under both control conditions and a salt treatment. I have calculated the decrease in lateral root ...
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11 views

suggest method for analysis of small sample data of fatigue

i am dealing with small sample data on fatigue. how to check inter dependence of data from small sample. how to analyse to reach a conclusion(confidence level estimation.) data points: ...
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15 views

feature selection in a small sample size

I need an advice. I have a dataset consisting of 108 observations (27 subjects * 4 time points) and ~10000 features. The data represents intensity values (comes from continuous domain). When I run ...
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54 views

ANOVA: testing assumption of normality for many groups with few samples per group

Assume the following situation: we have a large number (e.g. 20) with small group sized (e.g. n = 3). I noticed that if I generate values from the uniform distribution, the residuals will look ...
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21 views

Can I reuse the dataset set aside for performing t-test based on the following condition?

I have a small number of samples and large number features. For doing the feature selection I'm going to divide my total set into a feature selection set and a test set.I run the t-test on the former ...
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65 views
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How to test correlation of two variables from four repeated measures of each one among four groups

I have four plots from where I took a measure of two indicators of population abundance (as continuous variables) throughout four surveys (say, at spring 2010, fall 2010, spring 2011, fall 2011). So, ...
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1answer
84 views

The best model of an AICc-based model selection on a very small sample has an high number of predictors: does it make any sense?

I'm working with a very small sample size (N=14) and I'm using AICc to identify the most parsimonious model using a large number of possible predictors. Unexpectedly the best model has six predictors! ...
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20 views

How to analyse the ratio of two continuous variables sampled repeatedly over time

I am measuring reproductive hormones in dolphins over time to look at seasonal changes. The sample type (respiratory vapour) that I am using suffers from variable water dilution that cannot easily be ...
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36 views

Rare event sampling [closed]

Suppose $A$ is a very small subset of $\{0,\dots,n\}^3$ and I am trying to find an element of $A$. I first inspect maybe 50 random triples $(x_i,y_i,z_i), 1\le i\le 50$, and find that none of them are ...
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1answer
38 views

Estimate normal distribution from small sample with rankings

If I have n samples from an $N(\mu,\sigma)$ distribution, how can I estimate the distribution from a subset of m of these n samples where the order within those n is known. For example, if n = 100 ...
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1answer
51 views

Paired samples or independent sample hypothesis test for two time periods

I want to know if employees in an organization are surveyed in 2013 and again in 2014 if the samples from the two time periods are considered related and dependent or independent if they are asked the ...
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2answers
34 views

Do any statistical tests compare distributions when one has far fewer observations?

I've been researching different methods to compare two distributions for equality, or inequality rather. I want to compare actual user performance against projected performance, after a particular ...
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1answer
22 views

Using a measure of productivity which is determined by reviewers

Apologies for the ambigious title - I wasn't sure how a problem like this is expressed. I have a small sample of 20 individuals, of which the dependent variable (of interest) is binary with 5 ...
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40 views

OLS with dummy and few observations (12 mean values from 2.5k observations)

I have a dataset of 12 markets, in total ~2.5k trades happened over all markets. I now calculated 6 different measures for the each markets performance (my 12 observations per measure I want to use as ...
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0answers
27 views

Calibrated Probabilities for Outlier Detection Algorithm

I am currently developping a 2 class classification algorithm. However, as the dataset is at the moment really small (<50 observations) and imbalanced (~1/10 ratio), I decided to rather first ...
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1answer
167 views

Increasing sample size with bootstrap sampling

I'm trying to perform some classification analyses with a relatively small dataset (201 observations, 32 predictors). There are 8 classes in my data with unequal sample sizes ranging from 10 in the ...
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1answer
35 views

Size multilevel logit model

I want to estimate a multilevel logit model. But I'm confused about the minimum number of groups and observations per group. What would be the minimum number of observations per group? My case: I ...
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1answer
54 views

Using nonparametric tests with small samples even when data are normaly distrubuted

Is it appropriate to use a nonparametric test with a small sample (e.g., less than 65 people) even when data are normally distributed? For example, using the Spearman correlation? Actually my data is ...
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22 views

Small sample size : dealing with bootstraping for linear or nonlinear multiple regression

I am wondering to heal my ignorance from your experiences or your modeling knowledge. I have many matrices of quantitative variables, let me start with three matrices of proportions.To express ...
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18 views

Problem Approach: uncertainty about sample size

I have a time series of events (weekly aggregate date) Each event is information on contracts closed by a sales representatives during working weeks. The goal is to calculate what is the expected ...
4
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1answer
66 views

ANOVA-type test but with known population variance of each group

I have a set of $N$ samples $s_{i}$, each one sampled from a normal distribution with standard deviations $\sigma_i$, which are known. I would like to know if the distributions have the same mean. I ...
2
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1answer
66 views

MANOVA when sample size is smaller than the number of DVs

I need to compare $16$ quantitative variables, measured for two groups, A and B. I thought of applying MANOVA. However, there are only $4$ and $9$ cases for groups A and B respectively. I looked for ...
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9 views

Selecting the right DV in study of treatment effect on a small sample?

I want to run a simple experiment at work to see if making a single change F on a product, has any significant adverse effect on the performance. I need help to ...
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13 views

Optimizing selection from varying sets

On pages of website(s) I have a set of potential messages to choose from and only one or two slots to show them in. (think 'this product is on sale' or 'this product is new'). On each page the set ...
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34 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 ...
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1answer
16 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?
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73 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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11 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 ...
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1answer
496 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
71 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 ...
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1answer
21 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
16 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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81 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 ...
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1answer
83 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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26 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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61 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 ...
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1answer
63 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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21 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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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 ...
2
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1answer
68 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 ...
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4answers
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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 ...
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2answers
280 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 ...
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1answer
205 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 ...
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2answers
136 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 ...
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3answers
348 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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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 ...
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1answer
68 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
66 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 ...