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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1answer
16 views

Do Beta weights from regression have error terms?

I am looking at standardized regression weights (i.e., Beta weights). I was thinking of reporting the errors next to the weights in a figure, but upon some thought I was debating whether such errors ...
0
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0answers
12 views

White standard errors and Weighted Least Squares (WLS) [on hold]

Are there situations in which it would be useful to apply WLS and use White standard errors (from the transformed model) as well?
2
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0answers
47 views

Standard error of probability estimate

Take a look at Table 1 on page 268 in http://www.math.ku.dk/~rolf/teaching/thesis/DixonColes.pdf It says at the end of the previous page that the standard errors are computed "on the basis of an ...
1
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0answers
17 views

How to calculate standard errors of a non-linear model prediction?

I'm trying to understand how to show the prediction error of a model fit in R using the non-linear least squares function nls. Although there is an argument ...
0
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0answers
7 views

Newey–West estimator - Number of time observations needed

Are there some general rules, or Monte Carlo studies, that shows evidence of the approximate number of time periods needed to implement the Newey–West estimator?
0
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1answer
32 views

Standard error of a sum of two Poisson variables

I have 2 Poisson variables, I know mean and standard error for each. How do you calculate the Standard error of the sum?
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0answers
18 views

Finding multivariate clusters with survey data (in R)

I'd like to conduct a multivariate cluster analysis on data from the American Community Survey's PUMS microsample (individual level records). I've only performed cluster analysis before when there are ...
1
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0answers
14 views

Does residual autocorrelation beyond the first lag have any implication in a regular regression?

I have seen the review of a multiple regression analysis using time series with a quarterly frequency. The original modeler advanced that the model's residuals were not autocorrelated by disclosing a ...
0
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0answers
16 views

Linear regression slope confidence interval - how to choose a cutoff with few points?

I am performing a large number of linear regressions (around 2000) through the origin. Each regression is on a different number of points (between 2 and 1000), and I am using robust regression (with ...
0
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0answers
18 views

Please provide an example of when bootstrap has less bias than classically approximated estimates?

The recent question "Why does my bootstrap interval have terrible coverage?" has got me wondering if anybody has some really good examples of distributions in which bootstrapping standard errors ...
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0answers
61 views

Standard error of mean of gamma distribution

I am trying to determine whether the means of two Gamma distributions are significantly different. To do this, I am trying to determine the Wald Statistic as ...
1
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1answer
40 views

Analysing overdispersed data with generalised linear models

Let's say I have an explanatory variable and a response variable that represents counts. I want to see if the explanatory variable can predicts counts. I'm aware the response variable is ...
0
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0answers
15 views

Error computing Robust Standard errors in Panel regression model (plm,R)

I am using the plm library to run fixed effect regressions and the sandwich,lmtest libraries to compute robust standard errors. I have no problem running the regressions, but in some instances when I ...
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2answers
99 views

How is the formula for the Standard error of the slope in linear regression derived? [duplicate]

As stated in many textbooks, the Standard error of the slope in linear regression with one variable is $\sqrt{\frac{s^2}{SSX}}$ or some rewrite, ${s^2}$ being the error variance and ${SSX}$ being ...
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0answers
19 views

Standard errors in Fixed and Random Effects

If the appropriate model choice is Fixed Effects in a panel study, will the inference derived from the standard errors in an Random Effects model still be valid?
1
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2answers
34 views

How to interpret standard errors in a Cox model?

I am running a multi-variate Cox regression and Stata provides the standard errors for each hazard ratio. How are theses to be interpreted? I know that I want my coefficients to be large compared to ...
23
votes
6answers
283 views

Standard errors for lasso prediction using R

I'm trying to use a LASSO model for prediction, and I need to estimate standard errors. Surely someone has already written a package to do this. But as far as I can see, none of the packages on CRAN ...
1
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0answers
22 views

Margin of error for non-dichotomous data

I am trying to calculate the margin of error for specific survey questions. I know how to calculate this if the data are dichotomous (i.e., a 75-25 or 60-40 split). But how do you deal with questions ...
5
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2answers
51 views

Estimated standard errors for weak instrumental variable

I would like an explanation on the statement in bold below. At first glance, I'd think that a weak instrumental variable would yield a even bigger standard error estimate. "When instruments are ...
1
vote
1answer
44 views

Is it ok to compute statistics on t-values?

Background I have a population in which my dependent variable is binary with a highly-skewed distribution: Very few records are 1 (doers), most records are 0 (non-doers). I'm using logistic ...
2
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1answer
66 views

Understanding standard errors in logistic regression

I am having trouble understanding the meaning of the standard errors in my thesis analysis and whether they indicate that my data (and the estimates) are not good enough. I am performing an analysis ...
3
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1answer
74 views

Why does the standard error of the intercept increase the further $\bar x$ is from 0?

The standard error of the intercept term ($\hat{\beta}_0$) in $y=\beta_1x+\beta_0+\varepsilon$ is given by $$SE(\hat{\beta}_0)^2 = ...
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1answer
49 views

What does the standard error of my IV estimate tell me?

I have computed the IV estimate and the standard error of the IV estimate. Why do I care about its standard error?
2
votes
2answers
101 views

How to compute the standard errors of a logistic regression's coefficients

I am using Python's scikit-learn to train and test a logistic regression. scikit-learn returns the regression's coefficients of the independent variables, but it does not provide the coefficients' ...
3
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2answers
169 views

General method for deriving the standard error

I can't seem to find a general method for deriving standard errors anywhere. I've looked on google, this website and even in text books but all I can find is the formula for standard errors for the ...
4
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2answers
104 views

Deriving confidence interval from standard error of the mean when the data are non-normal

I have a small sample (n = 8), and I have calculated the mean and standard error of the mean. I don't know the underlying distribution of these observations, and I cannot assume it to be normal. I ...
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0answers
15 views

Understanding (1-mean(L) - c*(stderr(L))

I inherited some old programming code for a scoring mechanism and I am trying to understand it. The premise is that every user $u$ has receives many ratings from other users, all in the range $[0, ...
0
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1answer
15 views

Standard Errors in Winsteps: ERROR versus MODLSE

I am running anchored analyses in Winsteps on four data sets (a full data set as well as the data degraded by an additional 20%, 50%, and 70%). I noticed that the standard errors are labeled ERROR for ...
0
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0answers
18 views

Maximum Likelihood estimation with eps ~ t5 while eps ~ N(0,1)

If one estimates an ML model with eps following a t5 distribution, while the eps are actually standard normally distributed, intuitively I would say the estimated standard errors would be too large. ...
6
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1answer
62 views

When is the standard error of the mean impossibly large for a given data range, when we know the sample size?

While reading an article (published and peer-reviewed, referenced below) investigating proportions of different tissue types in the human brain I came upon a table presenting data on the different ...
1
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1answer
63 views

lsmeans vs. differences between lsmeans

I calculated the least-squares means and standard errors for a linear mixed model. I am attempting to plot the lsmeans and standard errors for the combinations of the two factors, but I notice a ...
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0answers
27 views

Best way to handle autocorrelation in residuals from panel data regression (FE)

What would be the best way to handle autocorrelated residuals in my panel data analysis (Fixed Effects). What I've tried: -Adding different regressors (no luck there), and besides the current model ...
3
votes
1answer
62 views

SE of fit versus SE of prediction

I would like to get the standard error on a prediction. Using R glm, I can get the SE of the fit for a specific prediction: ...
0
votes
1answer
45 views

How do i predict with standard errors using betareg package in R?

I'm using 'betareg' package in R to perform beta regression. predict() function with se.fit=T is supposed to return standard errors along with the prediction but it doesn't. Is there any other way I ...
1
vote
1answer
33 views

Correction of data reduces quality of results

I'm running a logistic regression with a small sample size: I corrected my data for outliers after checking the standard error (1.07) and the confidence intervall (0.51 - 11.55) for one of my ...
0
votes
1answer
60 views

How to derive the standard error of linear regression coefficient

For this univariate linear regression model $$y = \beta_0 + \beta_1x+\epsilon$$ given data set $D=\{(x_1,y_1),...,(x_n,y_n)\}$, the coefficient estimates are $$\hat\beta_1=\frac{\sum_ix_iy_i-n\bar ...
0
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0answers
42 views

confidence intervals for predicted values in linear regression [duplicate]

I have made this linear regression model: mtcars_lm <- lm(mpg ~ drat + hp, mtcars) Using the effects package, I can predict values of ...
4
votes
1answer
89 views

The Effect of Outliers

The following question comes up in robust statistics. There are two formula indicated below that I do NOT know how to derive. However, in order to make the context clear, let's start with the easiest ...
0
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0answers
35 views

confidence interval and sampling distribution for the mean

Ok, I'm having trouble with standard error, sampling distributions and confidence intervals. The question I am trying to answer is: How many holes do I have to drill in the ground to get good idea of ...
0
votes
1answer
58 views

Why is 30 touted as a sample size when the tables say otherwise?

If I have a population of 5000, statistics suggests that I need to sample about 350+ to get a confidence interval of 95% with margin of error 5%. So why do I see that sometimes we can get away with ...
0
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0answers
19 views

Large Standard error with no multicollinearity

I have two issues. First, I have ran a OLS, Poisson, and Negative Binomial Regression. For the OLS regression, I have multiple IVs (5 control and initially 2 predictor). For one of the predictor ...
1
vote
1answer
40 views

Different HC3 standard error estimates when normalising weights for weighted least squares fit using Python statsmodels

When I normalize the weights I use for fitting a line with weighted least squares, the parameters of the fitted line and the 'normal' standard errors stay exactly the same, as I would expect. The HC3 ...
2
votes
1answer
136 views

Standard errors in weighted least squares on aggregated data

I am interested - mostly just for my own knowledge, and not for any real problem - in the use of weighted least squares to estimate a model on individual-level data and aggregated versions of those ...
1
vote
1answer
43 views

estimating standard error for small sample sizes

I have generated a number of objects in 3D space (2D rectangles). I have sampled those objects along lines, calculating the number of intersections between the lines and objects. If I use increasing ...
0
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0answers
17 views

How to report multiple experimental observations each with their own error.

Hi I have experimental observations that look like this. The output is not a function of concentration, so I thought within each experiment they could just be considered repeated observations. ...
0
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0answers
96 views

Box and whisker plot or bar plot with mean and SE?

I am trying to present my data in a meaningful way. To do so, I thought it is a good idea to use a box and whisker plot, because, it shows min, max, median and skewness of data. However, due to ...
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0answers
21 views

How to link the SE(p) of the binomial distribution $B(n,p)$ to the SE(coefficient) in GLM?

This is a general question regarding GLM with binomial distribution. I use the following data (with $N=400$ observations) as an example (predict toxicity using treatment): ...
2
votes
0answers
42 views

Calculating standard error of a coefficient that is calculated from other estimated coefficient

I'm working on the Gompertz growth model to fit weight at age: $$ m(a)=m_{\infty}e^{-\gamma exp(-g{1}a)}$$ Where $m_{\infty}$ and $g_{1}$ are coefficients to be estimated. To deal with lack of ...
0
votes
1answer
56 views

Standard Error of MLE

I have a model and a vector of parameters that I estimate using ML. Since I'm doing a MonteCarlo I can simulate as many times as I want, i.e. data is not real data. I was just wondering how I can ...
0
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1answer
37 views

Is there a formula for the standard error of both the explanatory and response variables

I was reading a social science paper that tried to explain the correlation between two variables. In that reference there was mention of its standard-error and p-value and that got me to thinking ...