Observer error in sampling a rare plant population

Background: Estimation of abundance in vegetation sampling involving observers is almost always characterised by observer error, although such error is rarely reported.

Aims: To quantify observer error in population estimation of the rare plant species Physaria filiformis in Missouri, USA.

Methods: The abundance of P. filiformis was estimated within 25-m² plots by six trained observers with varying experience levels over 10 years. Observers assigned plots to six predefined density classes. A total of 477 plots were estimated annually, and actual counts were conducted on ca. 10% of the plots to assess per cent agreement of estimates with counts.

Results: Over a third of the estimates of plant abundance evaluated for accuracy (36.4%) deviated from exhaustive counts. The majority of the misestimates were underestimates by one density class (29.4%). The number and type of misestimates varied systematically with density class.

Conclusions: Observer error could be explained to some degree by variation in population density, but not by experience. It appears that inherent differences exist among observers that cannot be entirely compensated for by experience or training. Observer error in this system represents a systematic bias, and can be compensated for by use of correction factors, which would ideally be both density class-dependent and observer-specific.     

Comparing biomarker measurements to a normal range: when to use standard error of the mean (SEM) or standard deviation (SD) confidence intervals tests

This commentary is the second of a series outlining one specific concept in interpreting biomarkers data. In the first, an observational method was presented for assessing the distribution of measurements before making parametric calculations. Here, the discussion revolves around the next step, the choice of using standard error of the mean or the calculated standard deviation to compare or predict measurement results     

Comparison of three commercial dosimetric systems in detecting clinically significant VMAT delivery errors

AimTo study the sensitivity of three commercial dosimetric systems, Delta4, Multicube and Octavius4D, in detecting Volumetric Modulated Arc Therapy (VMAT) delivery errors.MethodsFourteen prostate and head and neck (H&N) VMAT plans were considered for this study. Three types of errors were introduced into the original plans: gantry angle independent and dependent MLC errors, and gantry angle dependent dose errors. The dose matrix measured by each detector system for the no-error and error introduced delivery were compared with the reference Treatment Planning System (TPS) calculated dose matrix for no-error plans using gamma (γ) analysis with 2%/2 mm tolerance criteria. The ability of the detector system in identifying the minimum error in each scenario was assessed by analysing the gamma pass rates of no error delivery and error delivery using a Wilcoxon signed-rank test. The relative sensitivity of the system was assessed by determining the slope of the gamma pass line for studied error magnitude in each error scenario.ResultsIn the gantry angle independent and dependent MLC error scenario the Delta4, Multicube and Octavius4D systems detected a minimum 2 mm error. In the gantry angle dependent dose error scenario all studied systems detected a minimum 3% and 2% error in prostate and H&N plans respectively. In the studied detector systems Multicube showed relatively less sensitivity to the errors in the majority of error scenarios.ConclusionThe studied systems identified the same magnitude of minimum errors in all considered error scenarios.     

Empirical best linear unbiased prediction in cultivar trials using factor-analytic variance-covariance structures

 Results of multi-environment trials to evaluate new plant cultivars may be displayed in a two-way table of genotypes by environments. Different estimators are available to fill the cells of such tables. It has been shown previously that the predictive accuracy of the simple genotype by environment mean is often lower than that of other estimators, e.g. least-squares estimators based on multiplicative models, such as the additive main effects multiplicative interaction (AMMI) model, or empirical best-linear unbiased predictors (BLUPs) based on a two-way analysis-of-variance (ANOVA) model. This paper proposes a method to obtain BLUPs based on models with multiplicative terms. It is shown by cross-validation using five real data sets (oilseed rape, Brassica napus L.) that the predictive accuracy of BLUPs based on models with multiplicative terms may be better than that of least-squares estimators based on the same models and also better than BLUPs based on ANOVA models. Received: 18 October 1997 / Accepted: 31 March 1998     

Reliability of reliability coefficients in the estimation of asymmetry

Although promising to provide insight into the interaction between genotype and environment, investigations into fluctuating asymmetry suffer from a lack of standardization in the reporting of measurement error. In the present paper we show, using both anthropometric and odonto-metric data, that the use of the reliability coefficient calculated for a bilateral measurement provides no indication of the reliability of the corresponding asymmetry estimate, because reliability of asymmetry depends on the relationship between measurement error and the difference between sides. Thus, we suggest that future investigations either provide reliability coefficients for asymmetry estimates specifically, or use methods that account for measurement error. © 1995 Wiley-Liss, Inc.     

Synapse elimination,the size principle,and Hebbian synapses

Synapse elimination at the vertebrate neuromuscular junction reduces a polyinnervated population of muscle fibers to a monoinnervated state. The function of this developmental phenomenon (if any) is unproven. A theoretical analysis of Hebbian (correlation) rules connecting presynaptic and postsynaptic activity and synaptic strength at the neuromuscular junction is presented. The following points are demonstrated: (1) Correlational competition leads to the reduction of polyinnervation to a stable monoinnervated state; (2) the competition gives rise to the size principle over a wide range of the plausible parameter space; (3) over a significant subrange, the competition selectively eliminates topographically incorrect synapses; and (4) in cases in which topographic projection errors overwhelm the system, both error correction and the development of the size principle are disrupted. Correlational competition may explain contradictory experimental results concerning the effects of stimulating or silencing subpopulations of motor neurons. It may also explain an otherwise puzzling instance of a breakdown in the size principle seen in humans undergoing neural regeneration. Taken together, these findings suggest a novel hypothesis for the function of synapse elimination at the neuromuscular junction: the establishment of the size principle. © 1995 John Wiley & Sons, Inc.