Lord’s paradox in latent change score modeling: an example involving facilitating longitudinal effects between intelligence and academic achievement

It has been claimed that intelligence causes academic achievement to increase over time, and that also, conversely, academic achievement causes intelligence to increase over time. This bidirectional facilitating longitudinal effect between intelligence and academic achievement rests on observed associations between initial intelligence and the change in academic achievement between an initial and a subsequent measurement, and vice versa. Here, we demonstrate, through simulating empirical data used in previous research, that such longitudinal associations may be due to regression toward the mean rather than a true facilitating effect. Regression toward the mean occurs due to the conditioning of change on the initial value on the outcome variable. Researchers should be aware of this fallacy and are recommended to verify their findings with analyses without adjustment for an initial value on the outcome.

Cricket Score Prediction Using Machine Learning

Currently, there is a system which can calculate the current run rate and from it calculates the final score of the team. It doesn’t consider the fact about the no of wickets and also where the game is being played. The problem with the current system is that it is unable to predict the score of the 2nd team and also unable to predict the win percentage This system which is developed will have 2 model in it the 1st model predict the score a team will get after playing 50 over from the current situation. The second method predicts the win percentage of both teams even before the match has started this done by player selection. We found that error in regression toward the mean classifier could be a smaller quantity than Naïve mathematician in predicting match outcome has been sixty-eight ab initio from 2-15 overs to ninety-one until the top of 42th over.

Diminished Returns of Parental Education in Terms of Youth School Performance: Ruling out Regression toward the Mean

Background: Minorities’ Diminished Returns (MDRs) refer to systemically weaker effects of socioeconomic status (SES) indicators on various developmental, behavioral, and health outcomes of ethnic minorities compared to non-Hispanic (non-Latino) Whites. Similar MDRs also exist for the effects of parental education on the school performance of ethnic minority youth. Aim: To assess whether regression toward the mean (RTM) has any role in explaining the diminished effects of parental education on the school performance of Black and Hispanic youth relative to non-Hispanic White youth. Materials and methods: Data for this cross-sectional study came from the Monitoring the Future survey (MTF, 2017), a nationally representative survey of American youth in 12th grade. The sample included 10,262 youth who were 12th graders (typically 17–18 years old). The independent variable was parental education with five categories: Some high school, High school graduate, Some college, College graduate, and Graduate school. The outcome was self-reported school performance measured as grade point average (GPA). Ethnicity was the effect modifier. Analysis of variance (ANOVA) and the Tukey Post Hoc test was used to analyze the data. Data visualization (line graphs) was used to visualize the shape of youth GPA as a function of parental education levels across ethnic groups. Results: While a perfect stepwise increase was seen in youth school performance as a result of parental education improvement, this pattern differed considerably across ethnic groups. Such a perfect stepwise increase in youth school performance as a result of the incremental increase in parental education was missing for Black and Hispanic youth. The shape of the association between parental education and youth school performance ruled out regression toward the mean (RTM) as an explanation for the observed diminished effects of parental education on the school performance of Black and Hispanic youth. Conclusion: Diminished returns of parental education on the school performance of Black and Hispanic youth cannot be explained by regression toward the mean. Other factors and contextual processes, such as segregation, discrimination, racism, and poor quality of schools in urban areas, should be investigated in future research.

Evaluation of wind park tax incentives in Colombia by means of real options

<p>The objective of this study is to assess tax incentives in Colombia to foster investment in wind parks. Fiscal incentives seek to diversify energy consumption with non-conventional renewable energy sources, since power is mostly generated by hydraulic force and since its price is impacted during dry seasons. The price of energy is modeled according to a regression toward the mean. This stochastic process was chosen because during droughts in Colombia there are price increases, which then return to their average value. This is an upward and downward spike behavior, as well as a regression toward the mean. Given price uncertainty and its impact on cashflow, wind parks were valued with real options to flatten the reversal for five years. The real option of flattening as an American call option was considered. Results show that, according to traditional valuation methods, wind parks in Colombia are not profitable even with tax incentives. However, according to the real options method, tax incentives do make these projects economically viable.</p>

Intelligence, consistency, and Emerson's dilemma

In a large representative sample of Swedish male conscripts (N = 49,246), we demonstrate a positive association between intelligence and response consistency on items measuring endorsement of a strong military defense. This association is accentuated, to some degree, by an apparent difficulty to handle reversed items among those with low intelligence. Consequently, due to regression toward the mean, reversed items in measurement instruments would tend to have a negative effect on statistical power when analyzing the association between whatever the instrument is measuring and intelligence. On the other hand, the presence of reversed items could mitigate bias in the measurement due to an acquiescent response style among those with low intelligence. Lack of motivation/carelessness and inadequate reading ability among some subjects are two possible confounders for the found association in the present study.

Being Surprised by Regression Toward the Mean

We are predisposed to discount the role of luck in our lives—to believe that successes are earned and failures deserved. We misinterpret the temporary as permanent and invent theories to explain noise. We overreact when the unexpected happens, and are too quick to make the unexpected the new expected. The key to understanding regression toward the mean is to look behind the data—to recognize that when we see something remarkable, luck was most likely involved and, so, the underlying phenomenon is not as remarkable as it seems. Not to be confused with the gambler’s fallacy where good luck is followed by bad luck, regression toward the mean states that extremely good luck is generally followed by less extreme luck. The Sports Illustrated jinx is nothing more than this. Whenever there is uncertainty, people often make flawed decisions due to an insufficient appreciation of regression toward the mean.