Refers to the standard deviation of the sampling distribution of a statistic calculated from a sample. Standard errors are often required when forming confidence intervals or testing hypotheses about the population from which the statistic was sampled.

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29 views

Confidence interval for a proportion

Let's say I want to built a confidence interval for a proportion. I have seen that many times this is made from the standard error: $1.96\pm SE$ taking SE from $SE=\sqrt{(p(1-p)/n)}$ But I guess ...
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12 views

How to interpret standard errors and t-values in error-correction terms?

When estimating a Vector Error Correction (VEC) model in EViews, the resulting output always shows the error-correction terms together with standard errors and t-values for the included variables, and ...
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1answer
22 views

SPSS - Calculation of confidence intervals in estimated marginal means of repeated measures ANOVA

I used SPSS to do a repeated measures ANOVA including one within- and one between subject factor. Let's say the between-subject factor is treatment group with levels treatment and control, and the ...
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0answers
17 views

Distribution of Standard Deviation of 2 Variable Linear Regression

Assuming we have a fit: $\hat Y= \alpha + \beta (X-\bar X)$ Such that: $Y_i=\alpha+\beta(X_i-\bar X)+\varepsilon$ The standard deviation of $\varepsilon$ is $\sigma$. Estimated in an unbiased way ...
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7 views

PROC LCA fail to calculate standard error

I am using PROC LCA in SAS to run latent class analysis on a dataset with 20 binary variables. However, I got such warnings: WARNING: The information matrix could not be inverted during standard ...
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10 views

Is this estimator for the standard error of a sample mean difference biased and what is the relation to Student's t-test?

In the situation of two indepdent samples, the variance of the difference in sample means $\bar{x}_1$ and $\bar{x}_2$ is $$Var(\bar{x}_d)=\frac{\sigma_1^2}{n_1}+\frac{\sigma_2^2}{n_2}=\sigma_d^2$$ and ...
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1answer
182 views

Why doesn't the standard deviation represent a normal distribution?

Why doesn't the standard deviation of a sufficiently large sample represent a normal distribution that we can make inferences from? Let me list my thought process, so hopefully someone can highlight ...
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12 views

Combining two estimates of variance

I have a sample of N stocks, and a sample period of length T. At each time $t$, I have the following information: For each stock i, I have an estimate of variance (of returns) ...
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1answer
46 views

Confused about the basics - distributions and standard error

I've spent some time trying to understand what it is that statisticians are doing when they get a point estimate, and relate it back to some population parameter. I can do the calculations and ...
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33 views

If the sample standard deviation and standard error are biased estimators, why are they still so useful?

The sample standard deviation and standard error of the mean are biased estimators for their corresponding population population parameters. As explained here for the sample standard deviation this is ...
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1answer
33 views

The difference between the standard error of the sample and the standard error of the mean value

I have an assignment that gives 48 counts of the same phenomena occurring over the same time interval. I am asked to a) Calculate the mean of the counts b) Calculate the standard error of the sample ...
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1answer
202 views

How to use delta method for standard errors of marginal effects?

I am interested in better understanding the delta method for approximating the standard errors of the average marginal effects of a regression model that includes an interaction term. I've looked at ...
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55 views

Confidence intervals for median

I have a distribution of samples with a small number of values in each one (less than $10$). I have calculated the median for each sample, which I want to compare with a model and obtain the ...
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2answers
30 views

Using variance from a Jeffreys prior in a Prevalence meta-analysis

I am doing a meta-analysis on a group of studies, where the observation is a rate (no. of successes / no of trials). Some of the studies have small sample sizes (n<10) and/or did not observe any ...
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0answers
30 views

Given a covariance matrix from a Linear regression, how do I calculate the standard error of the coefficients?

I have an OLS with autocorrelation in the residuals. I'm using python statsmodels, and found that there is the sandwich_covariance matrix, which can cal Reference to Newey-West covariance matrix: ...
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1answer
62 views

Is the convention for error bars to present one or two standard errors?

I am plotting error bars in ggplot2 with geom_bar and geom_errorbar. geom_errorbar asks for ...
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0answers
7 views

Tools for determining final error with mixture of correlated and independent sources of error

Preface: Not looking for an answer, but rather seeking an approach or set of approaches to deal with a complicated problem. Brief version: I have a single, analytical set of 3 equations with 8 ...
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21 views

Aggregating Standard Errors for Predicted Probability Estimates

I obtain predicted values from a logistic regression for a certain outcome (e.g., mortality) at the hospital level – the data is at the patient level – and need to compute the average across ...
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13 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
83 views

Estimating standard error of parameters of linear model fitted using gradient descent

Given a linear model $$y = X\beta + \epsilon$$ we can estimate parameters $\hat{\beta}$ using two different ways - ordinary least squares (OLS) and gradient descent (GD). Both of them boil down to ...
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2answers
194 views

What causes non-normality of the error term in OLS?

In data, what causes the error term to be non-normally distributed in regression? Along the same lines, what solutions are there for non-normal residuals? For example, is it caused solely by a ...
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2answers
67 views

R - how to get standard error for a breakpoint/parameter in a piecewise regression

I'm new to asking questions here, so I hope this is a reasonable place for this. I am trying to fit a piece-wise regression. I expect my response (y) to increase from x0 to somewhere along x, then to ...
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2answers
50 views

Logit Standard Error

What is the SE of logit transformed variable $p$? $logit = \log\frac{p}{1-p}$ where $p = \frac{n}{N}$ Is it: $se = \sqrt{\frac{1}{n} + \frac{1}{N-n}}$
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14 views

Find the standard error in a two-tailed test without knowing the standard deviation

I have an A/B test and I need to find the standard error for each in order to compute the upper and lower bound at a 95% confidence level. The issue is that I don't have access to the individual ...
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1answer
41 views

Interpreting the value of standard errors [duplicate]

After computing the standard error of regression, my answer is 3.55 what does the value mean
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1answer
62 views

Selecting priors based on measurement error

How do you calculate the appropriate prior if you have the measurement error of an instrument? This paragraph is from Cressie's book "Statistics for Spatio-Temporal Data": It is often the case ...
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1answer
33 views

Does the calculation of error bars in lme4 require the Cosineau (2005) correction?

In Cosineau (2005) a method for calculating within-subject design error bars which removes the between subjects variance before calculating confidence intervals, error bars and so on is suggested. I ...
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19 views

Appropriate relative standard error interpretation/calculation

To estimate the proportional change from a reference value for a given covariate, I am trying to understand which method is more appropriate from an interpretation of the precision of the estimate. ...
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57 views

OLS standard error that corrects for autocorrelation but not heteroskedasticity

Question: By mapping the OLS regression into the GMM framework, write the formula for the standard error of the OLS regression coefficients that corrects for autocorrelation but not ...
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1answer
212 views

Why don't we use the unbiased sample variance to calculate the standard error?

The standard error is an approximation of the standard deviation of the sampling distribution of the sample means. The real standard deviation of the sampling distribution, $\sigma _{\bar x}$ is: ...
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12 views

logarithmic calibration and geometric mean - citation search

I have a logarithmic calibration line: MachineSignal = -3.21 log(concentration) + 21.9 It seems obvious to me, that if I have a triplicate measurement of concentrations (measured indirectly through ...
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9 views

How to calculate MoE for subsamples

I have demographic and income data for 3 million people from the American Community Survey (courtesy of IPUMS), and my goal is calculate the median income for every permutation of age group, gender, ...
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2answers
179 views

Why do we have to assume normality for a one-sample t-test?

As a consequence of the central limit theorem the sampling distribution of the sample means will always be normal whatever is the distribution of the variable we measure. From our sample we can ...
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1answer
75 views

Standard error of proportions, with weighting

I have a set of experiments $i=1\dots k$ each of which performs $n_i$ binomial experiments, recording a fraction $p_i$ successes. Clearly if I trust all of the experiments equally, my estimated ...
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30 views

histograms/ kernel density estimation for proportion data

I am looking at digital advertising data with the following columns: site_id | impressions_count| clicks_count. I am interested in a histogram of the click through rate (clicks/impressions) across ...
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1answer
113 views

Standard error bars overlap but significance - estimated marginal means versus observed means

I'm running a Mixed effects model ANOVA with two fixed factors (condition, repetition) and one random factor (subject). Subsequently, a Tukey multiple comparisons test is performed. Now I'd like to ...
2
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1answer
142 views

Why autocorrelation affects OLS coefficient standard errors?

It seems that OLS residuals autocorrelation is not always an issue, depending on the problem at hand. But why residuals autocorrelation would affect the coefficient standard errors? From the Wikipedia ...
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2answers
123 views

How can I calculate t-score without knowing true population mean?

I am studying now t-scores. As far as I understand, t-scores are used when we don't know true population parameters (such as: standard deviation and population mean) and cant use z-scores. Here is ...
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0answers
196 views

Calculating the Net Promoter Score for poll data on a 1-5 scale

From Wikipedia The Net Promoter Score is obtained by asking customers a single question on a 0 to 10 rating scale, where 10 is "extremely likely" and 0 is "not at all likely": "How likely is ...
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2answers
100 views

How to compute (or numerically estimate) the standard error of the MLE

I have a model for which I know the log likelihood function, the gradient of the log likelihood and the Hessian of the log likelihood. For given data I can compute the MLE using a generic optimizer ...
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1answer
25 views

Assuming the true mean

I've collected fluorescence data from some bacterial cells. Each cell has a gene in it which can be induced to fluoresce. However, even without being induced, the gene will still fluoresce a little. ...
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1answer
30 views

Adjust standard errors for within correlation

I am trying to replicate a table and in one of the notes it's written that 'standard errors are adjusted to account for the within-analyst correlation of the observations' I am running my regressions ...
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3answers
82 views

Analytic or sample standard deviation with binomial data

I've been looking for recommendations on whether it's better to use the sample standard deviation (SD) for a binomial distribution or use the analytic SD (or variance). It's for experiments with ...
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0answers
10 views

Standard error for expected value [duplicate]

I have a computer simulation from which I get a sample of values of some microscopic quantity $X$, i.e. $\{ x_1,\ldots,x_N \}$. I'm interested in estimating the expected value of $X$, i.e. $E[ ...
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22 views

Mean squared error / Max error squared

I'm use this metric for variation that is similar to CV, but it is guaranteed to be on a 0 to 2 scale for positive numbers, where 2 is "all over the place" and 0 is "perfectly even". Since its ...
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0answers
11 views

error on truncated rms

I am computing the RMS of a sample to estimate the standar error $\sigma$ of the underlying distribution (for simplicity let say a normal distribution $N[\mu$, $\sigma$]). $ \text{RMS} = \sum_{i=1}^N ...
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26 views

Proper back-transformation of lognormal standard deviation to find confidence intervals around a mean [duplicate]

I want to determine the 95% confidence interval of a mean. I logged-transformed my data in order to achieve a normal distribution. Several observations contained 0, so I changed these to 1 so that ...
3
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2answers
40 views

Standard error of mean for a distribution with two dependent variables

I want to calculate the mean and standard error of the mean for the amount spent per person visiting a store. Most people don't buy anything, so the distribution looks like this ${\rm P}({\rm ...
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37 views

How does Standard Deviation (Error) change with sample size change in this scenario. Explanation needed for a nonprofessional

I have this question that I want figured out. A person's Blood pressure was taken 4 times,the mean of these 4 observations came out to be say 120mm of Hg And the SD was 2.5. Now we have taken 4 more ...
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13 views

Obtaining Standard Error of Weighted Averages using Bootstrapping?

My problem is finding a way to estimate the standard error of a flow-weighted mean concentration. The FWMC is computed by summing the years flow * concentration measurements and dividing by the sum of ...