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# Category Archives: Stats

## The Use of Tobit and Truncated Regressions for Limited Dependent Variables

The OLS regression is a widely applied technique, and many variants of the classical regression exist. Among them, are the tobit and truncated regressions. Their use is recommended when the dependent (Y) variable is constrained in some ways. Both have … Continue reading

Posted in Stats

## How to calculate and use predicted Y-values in multiple regression

I was planning to publish this article after my paper on the black-white vocabulary gap in the GSS is released, but I have changed my mind. So, here, I will explain how to use the so-called “Yhat” or predicted values … Continue reading

Posted in Stats, Stats, Softwares, Syntax
Tagged GSS

## Get (not so easily) introduced to R

I dislike R, unlike some other softwares I use, such as SPSS and Stata. It’s extremely error prone. But it’s free, and can do almost everything (e.g., a few things Stata cannot do and a lot of things SPSS/AMOS cannot … Continue reading

## Get (easily) introduced to SPSS

I do not want to make multiple posts on this topic. So, this post will be updated little by little (if I learn something new). Here, we have a list of essential commands for creating variables, making basic (and advanced) … Continue reading

Posted in Stats, Stats, Softwares, Syntax
Tagged SPSS

## Get (easily) introduced to Stata

I do not want to make multiple posts on this topic. So, this post will be updated little by little (if I learn something new). Here’s the list of essential commands for creating variables, making basic (and advanced) statistical analyses.

Posted in Stats, Stats, Softwares, Syntax
Tagged Uncategorized

## Error Correction Model in Time Series Regression

A strong assumption of time series regression, a widely used technique in econometrics, is the stationarity. It requires that the variables entered in the regression have their variances (standard deviations), covariances (auto-correlations), and means, that are independent of time. A … Continue reading

Posted in Stats
Tagged Uncategorized

## Data Preparation. Matrix non Positive Definite in SEM Softwares.

I have previously reported a discussion about the non-positive definite matrix with regard to factor analysis. Here, I report a more complete, deep explanation and possibility to deal with these problems. This is not restricted to SEM but also can apply … Continue reading

Posted in Stats

## The Fallacy of Significance Tests

It must be known that a p-value, or any other statistics based on the Chi-Square, is not a useful number. It has two components : sample size and effect size. Its ability to detect a non-zero difference increases when either … Continue reading

Posted in Stats

## Multiple Regression, Multiple Fallacies

It goes without saying that multiple regression is one of most popular and applied statistical methods. Thus, it would be odd if most practitioners among scientists and researchers do not understand and misapply it. And yet, this provocative conclusion seems … Continue reading

Posted in Stats

## Genotype-Environment Correlation and IQ

Genotype-Environment Correlation and IQ John C. Loehlin and John C. DeFries Received 22 Feb. 1986–Final 22 Jan. 1987 The estimation of various forms of genotype-environment (GE) correlation is considered. Two methods of estimating “passive” GE correlation from adoption studies are … Continue reading

Posted in Behavioral Genetics, Stats
Tagged IQ