Sentences with phrase «by regression to the mean»

Not exact matches

A home - heavy schedule, excellent basketball by Bradley prior to an enormous regression to the mean, excellent basketball from Tobias before a similar but substantially smaller regression, hot shooting by Tolliver, Ish (for him) and Galloway, an offense that opponents hadn't already totally figured out, and overall solid health (sans perhaps Bradley's pre-absence groin injury, which was of unspecified severity).

Funnel plots, the Egger (weighted regression) test, and the Begg and Mazumdar (rank correlation) tests for funnel plot asymmetry were conducted to examine the relation between sample size and observed mean differences in blood pressure by infant feeding group (21).

If a process is meant to improve the integrity of the electoral process, judgments that shoot it down can not advance the cause of our development; it means we have chosen a path of regression to the era where elections are decided by unsavory self - help in bloating the voter register with strange names on the part of politicians.

Statisticians explain the changes, regardless of direction, by claiming «regression to the mean.»

If there were no difference between the gains experienced by F schools and those among low - performing non-F schools, we might worry that regression to the mean was driving our results.

Another potential explanation for the exceptional gains made by schools facing voucher competition is that their extremely low initial scores are affected by a statistical tendency called «regression to the mean.»

In reading, however, we found no difference in the test - score gains achieved by F schools and low - performing non-F schools, suggesting that regression to the mean could be influencing our results in reading.

Based on recent information provided by the Accountability Technical Advisory Committee's (TAC) recommendations to ISBE, it is likely that ISBE will move away from linear regression toward Student Growth Percentiles (SGPs) as a means to measure student growth under the new school improvement and accountability system.

They play the game of relative value, by using strategies such as regression to the mean.

«Regression to the mean is the most powerful law in financial physics: Periods of above - average performance are inevitably followed by below - average returns, and bad times inevitably set the stage for surprisingly good performance.»

Perhaps it's my age (I remember when I had do do linear regressions with a pencil and paper for the sums, and a slide rule to help with the squares and square roots), but a fundamental principle of a linear least squares regression is that the best fit line passes through the point represented by the mean X and mean Y values.

A recent paper by Loehle & Scafetta (L&S 2011) in a journal known as the «Bentham Open Atmospheric Science Journal «(also discussed at Skeptical Science) presents some analysis using regression to describe cycles in the global mean temperature, showing us many strange tricks one can do with curves and sinusoids, in something they call «empirical decomposition» (whatever that means).

The data is annual data from 1955 to 1995, with a mean of 23.025 C, a Standard Deviation of 0.2981 C, and a trend of 0.05 + / - 0.08 C / 10 years, as determined by simple linear regression.

a Regressions of winter SLP and SAT trends upon the normalized leading PC of winter SLP trends in the CESM1 Large Ensemble, multiplied by two to correspond to a two standard deviation anomaly of the PC; b CESM1 ensemble - mean winter SLP and SAT trends; c b − a; d b + a. SAT in color shading (°C per 30 years) and SLP in contours (interval = 1 hPa per 30 years with negative values dashed).

This range is constructed by computing the standard deviation (σ) of the 40 regression values at each grid box for each variable (SLP, SAT and P) based on detrended data during 1920 — 2012, and subtracting / adding these values (multiplied by two) from / to the ensemble mean regression value.

Central tendency, or reversion (regression) to the mean, says exactly you can subtract problems by adding them together and averaging them away, if you do it competently.

Annual trends are calculated by averaging the monthly mean anomalies together and fitting the regression to the annual average timeseries.

«A strong warming and severe drought predicted on the basis of the ensemble mean of the CMIP climate models simulations is supported by our regression analysis only in a very unlikely case of the continually increasing AMO at a rate similar to its 1970 — 2010 increase» 7

An exploratory analysis was to be performed by means of multiple regression with the dependent variable as the sum on the new scale and the independent variables as 14 personality disorder scales defined in DSM - 5, DSM - IV - TR, and DSM - III - R.

We implemented unadjusted and adjusted analyses (potential prognostic factors listed in table 2) of the outcomes (all quantitative) by using random effects linear regression models fitted by maximum likelihood estimation to allow for the correlation between the responses of participants from the same maternal and child health centre.29 We present means and standard deviations for each trial arm, along with the mean difference between arms, 95 % confidence intervals, and P values.

Logistic regression analyses were conducted to investigate the mediation hypotheses, using an established 3 - step procedure.48 First, we investigated whether there was a significant bivariate association between a high level of maladaptive parenting (operationally defined as ≥ 3 maladaptive parenting behaviors) or abuse during childhood or early adolescence (by a mean age of 14 years) and risk for suicide attempts during late adolescence or early adulthood (reported at a mean age of 22 years) and whether the magnitude of this association was reduced when interpersonal difficulties during middle adolescence (reported at a mean age of 16 years) were controlled statistically.

Effect sizes for combining results are within treatment and therefore inflated by sources of bias (eg, type I error of diagnosis, regression to the mean, and improvements not from therapy).

A decomposition methodology examined the contribution from different sources in explaining the SES gradient in early cognitive outcomes.34 Similar to the methodology used in the UK Millennium Cohort Study, we focus on the quintile 1 — quintile 5 (Q1 — Q5) and quintile 1 — quintile 3 (Q1 — Q3) gaps and calculate the percentile points and the percentage of the raw gaps explained by each candidate explanatory factor and each domain of factors.2 This was done by taking the product of the mean gap in each explanatory factor (mean difference between Q1 — Q5 and Q1 — Q3) by the β coefficients from linear regression models that predict reading and math ability from SES and all candidate explanatory factors.

According to the procedures posed by Aiken and West (1991), we used the simple slope for the regression of self - esteem on general family function by using the high (one standard deviation above the mean) and low (one standard deviation below the mean) values for social support.