Sentences with phrase «for regression to the mean»

With so many cheap stocks to choose from in 2009, even value managers who didn't want to buy financials could easily build a portfolio full of cheap stocks and wait for regression to the mean.

Not exact matches

Either it'll be a new normal for the player (which is not predictable) or it'll be a regression to the mean.

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).

But considering how poor this unit was for much of the year, we'll assume improvement, from a progression - to - the - mean standpoint, is more likely than regression.

We also estimated relative indices of inequality (RII) and slope indices of inequality (SII) as summary measures of relative and absolute inequalities of breastfeeding outcomes, respectively, across the entire distribution of maternal education.24 For child IQ, linear regression analyses using GEEs were performed to estimate mean IQ differences in lower maternal education from the reference category in each intervention group and compared between the groups.

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).

After log - transforming total IgE, linear regression was used to estimate geometric mean ratios for IgE; confidence limits were calculated using Huber variances.

It may be harder to code and analyze essays about paintings than to run another value - added regression on the math and reading scores that the centralized authorities have collected for us, but that doesn't mean it's any less important.

These coefficients differ from the mean special education rates in Figure 1 because they refer to differences from the mean for whites, the excluded group in the regressions.

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.»

Or perhaps a flood of new investment capital over the last decade or so has produced a lofty ending valuation, which has yet to mean revert, 12 and which would lead the regression to underestimate the true power of valuation for the low beta factor.

«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.»

For instance, a reasonable expectation based on forward price - to - earnings data might be a 25 % bearish downturn whenever regression to the mean comes to pass.

This tendency for trends to flip with the passage of time is called regression to the mean.

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.

I have linearly extended the ensemble mean model values for the post 2003 period (using a regression from 1993 - 2002) to get a rough sense of where those runs might have gone.

As it is, a forcast for 2005 based on OLS regression for 1988 to 2006 has a mean of 0.61 C with a 95 % CI from 0.37 C to 0.84 C.

Whether linear or curvilinear correlations, and regardless of the regression method, or outlier elimination process for values in a data set + / - 3 s.d.'s from the mean, error analysis and going back to raw data are essential procedures.

Hamilton, 4.0 + / - 0.3, Statistical A simple regression model for NSIDC mean September extent as a function of mean daily sea ice area from August 1 to 5, 2012 (and a quadratic function of time) predicts a mean September 2012 extent of 4.02 million km2, with a confidence interval of plus or minus.32.

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.

If we have, indeed, only had polar ice for 20 % of the last 6 - million years (from Ian Plimer), then regression - to - the - mean dictates betting on «up» would likely yield better odds at times when we have ice caps to ponder.

We blended surface meteorological observations, remotely sensed (TRMM and NDVI) data, physiographic indices, and regression techniques to produce gridded maps of annual mean precipitation and temperature, as well as parameters for site - specific, daily weather generation for any location in Yemen.

The least - squares linear - regression trend on the RSS satellite monthly global mean surface temperature anomaly dataset continues to show no global warming for 18 years 9 months since February 1997, though one - third of all anthropogenic forcings have occurred during the period of the Pause.

For example, the fact that UAH / RSS slower warming in the 2000s has coincided with a solar minimum means that a regression is going to attribute the former to the latter, even though it might not be causal (although it probably is).

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).

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.