Sentence examples for methods produced estimated from inspiring English sources

It was notable that different data bases and need for separate statistical methods produced estimated incremental costs that did not vary greatly.

With high observer reliability, both methods required surveying approximately 0.26% of the study area (0.26 km2 out of 100 km2 in this simulation) to achieve an accurate estimate of population size; at or above this sampling effort both methods produced estimates within 33% of the true population size 50% of the time.

Excluding BitSeq (MCMC and VB) and Casper, we see that many methods produced estimates close to the boundary of the parameter space, as seen in Figure 5.

Considering the between-imputation variance ((1 +  1/ m ) E [ B m ]), although the non-rounded regression and truncated regression methods produced estimates close to the variance of Q ¯ m across the 1000 replications, post-imputation rounding and predictive mean matching both produced under-estimates of the actual between-imputation variance.

These methods produce estimates that are superior to those of the older methods, but for many researchers, multiple imputation is the general solution to missing-data problems in statistics (Rubin, 1996; Schafer, 1997).

The two methods produce estimates of similar magnitude when standardising by age and sex.

The simulation results validate our two proposed methods, producing estimates close to the preassigned values.

Propensity score methods produce estimates that are more accurate than logistic regression estimates when there are seven or fewer events per confounder, as was the case in the present study [ 24].

While previous literature has shown that regression methods produce estimates with a higher mean square error and have less power (Kao, 2000), these results apply primarily to the case of interval mapping when the spacing between markers is wide (>1cM).

These methods produce estimates of migration rates (m) or moments of the distribution of dispersal distances (such as σ, the standard deviation of axial dispersal distances, Box 2) which can be difficult to interpret in an ecological context.

While this underestimation is undesirable, it is important to keep in mind that this method produced estimates of summer prey acquisition rates that were, on average, 85% (number of prey) and 62% (biomass of prey) greater than estimates based on data obtained through a single GPS-collared wolf.