Sentences with phrase «random coefficient»

The final data analysis was conducted using random coefficient regression analysis, which is a subset of the mixed model that is useful for longitudinal data.

The relation between adolescent alcohol use and peer alcohol use: A longitudinal random coefficients model

Not exact matches

Crandom and Lrandom were computed as the average clustering coefficient and characteristic path length of a set of h random graphs with a comparable total degree and degree distribution as that of the examined functional connectivity graph (supplemental material, available at www.jneurosci.org).

Networks with a small - world organization have a clustering coefficient C that is much higher than the clustering coefficient of a comparable random organized network, but still with a short characteristic path length L that is similar to that of an equivalent random organized network (Watts and Strogatz, 1998).

Formally, small - world networks show a ratio γ defined as C / Crandom of ≫ 1 and a ratio λ defined as L / Lrandom of ∼ 1, with Crandom and Lrandom the clustering coefficient and characteristic path length of a random organized network of similar size (Watts and Strogatz, 1998; Sporns et al., 2004).

We discuss how correlation can be quantified using correlation coefficients (Pearson, Spearman) and show how spurious corrlations can arise in random data as well as very large independent data sets.

These are no frills differentiated worksheets on simultaneous equations containing the following: ★ Adding only where x or y have a positive coefficient of 1 ★ Subtracting only where x or y have a positive coefficient of 1 ★ Mix of adding or subtracting where x or y have a positive coefficient of 1 ★ Mix of adding or subtracting where x or y have a positive or negative coefficient of 1 ★ Adding and subtracting where either the x or the y will be a multiple of the other ★ Adding and subtracting where either the x or the y will be a multiple of the other including negative numbers ★ The coefficient of x and y are totally random.

• solve simultaneous equations where the coefficient of x OR y is a factor of the other x or y E.g. 4y + 7x = 117 2y + 2x = 40 There are 2 medium sheets — one with negative answers, one without • solve simultaneous equations where x and y are random integers or decimals E.g. 4y - 3x = 34.5 6y + 5x = 56.5 There are 2 hard sheets — one with negative answers, one without Features: - Print the questions off - Print the answers off - Refresh the questions so you get any entirely new set of questions and answers (unlimited questions!)

The terms αt and βg are year - of - test and grade - of - test effects, while Xi is a vector of demographic controls with coefficient γ, and εigt is an error term that reflects random fluctuation in test scores.

I am reminded of the «random walk of an object through an infinite array of discrete boxex... Bernouli coefficients and so forth.

Here we demonstrate that statistical models based on random - coefficient regressions are able to emulate ensembles of process - based crop models.

They observe that pseudoproxy tests limited to low - order AR1 noise insufficiently replicate observed proxies and conduct more testing simulations using «empirical AR1» coefficients and brownian motion (random walk) pseudoproxies.

As estimated through various methods, the lag - one correlation coefficient used to generate the random null proxy sets is usually set between 0.2 and 0.4.

if you've got a bivariate random parameters (intercepts and age effects) up and running, and so can estimate a correlation or covariance between initial growth rate (the tree - specific random additive effect at age = 1) and tree - specific random age coefficient across the sample, the significance of that correlation / covariance would be a first crack at this without choosing an age at which to split the sample.

The two images below (if my links work properly) are of the age effect and year effect coefficients with 95 % (2se) error bands, from a random effects model on data from 1000 - 1996.

In that model, each observation is regressed linearly on the previous observation, and the regression coefficient is a random effect (i.e., it varies between persons).