A comparison of methods for estimating the lactate threshold

The purpose of this study was to examine the accuracy of tests that may be used by distance runners to estimate the lactate threshold. Competitive distance runners/triathletes (N = 27) performed a criterion test that directly measured (blood lactate of 4.0 mmol.L(-1)) the lactate threshold. Subjects then performed 4 tests (VDOT, 3,200-m time trial, 30-minute time trial, Conconi) that estimate the threshold. Mean estimations of the running velocity at the lactate threshold from the 30-minute time trial (standard error of the estimate, SEE, 0.21 m.s(-1)) and VDOT (SEE 0.41 m.s(-1)) methods did not differ (P>0.05) from the criterion. In terms of heart rate, the 30-minute time trial estimation did not significantly differ (SEE 8.0 b.min(-1)) from criterion. These findings suggest that the 30-minute time-trial method should be considered by coaches and distance runners/triathletes as a method for estimating both the running velocity and heart rate at the lactate threshold.     

Evaluation of several methods for estimating phylogenetic trees when substitution rates differ over nucleotide sites

Several maximum likelihood and distance matrix methods for estimating phylogenetic trees from homologous DNA sequences were compared when substitution rates at sites were assumed to follow a gamma distribution. Computer simulations were performed to estimate the probabilities that various tree estimation methods recover the true tree topology. The case of four species was considered, and a few combinations of parameters were examined. Attention was applied to discriminating among different sources of error in tree reconstruction, i.e., the inconsistency of the tree estimation method, the sampling error in the estimated tree due to limited sequence length, and the sampling error in the estimated probability due to the number of simulations being limited. Compared to the least squares method based on pairwise distance estimates, the joint likelihood analysis is found to be more robust when rate variation over sites is present but ignored and an assumption is thus violated. With limited data, the likelihood method has a much higher probability of recovering the true tree and is therefore more efficient than the least squares method. The concept of statistical consistency of a tree estimation method and its implications were explored, and it is suggested that, while the efficiency (or sampling error) of a tree estimation method is a very important property, statistical consistency of the method over a wide range of, if not all, parameter values is prerequisite.     

A comparison of methods for estimating mean fecundity

Four computational methods for estimating mean fecundity are compared by Monte Carlo simulation. One of the four methods is the simple expedient of estimating fecundity at sample mean length, a method known to be downwardly biassed. The Monte Carlo study shows that the other three methods reduce bias and provide worthwhile efficiency gains. For small samples, the most efficient of the four methods is a 'bias adjustment', proposed here, that uses easily calculated sample statistics. For large samples, a numerical integration method has the highest efficiency. The fourth method, a 'direct summation' procedure which can be done easily in many statistical or spreadsheet programs, performs well for all sample sizes.     

Nonparametric estimation of the survival function when cause of death is uncertain

A nonparametric estimator for the survival function, accommodating censored survival times and uncertainty in the assignment of cause of death, is proposed. For example, in a carcinogenicity experiment the data on each animal may consist of an observed age-at-death and some indication of the probability that the tumor type under study caused death. An estimator of the net survival function, for time-to-death due to the cause of interest, is developed. Under certain assumptions, the proposed estimator is consistent and asymptotically normally distributed. Monte Carlo simulations were used to compare this estimator with the Kaplan-Meier estimator. Forcing the cause of death to be specified with certainty, as required by the Kaplan-Meier estimator, may result in substantial biases.     

General right censoring and its impact on the analysis of survival data.

This paper concerns general right censoring and some of the difficulties it creates in the analysis of survival data. A general formulation of censored-survival processes leads to the partition of all models into those based on noninformative and informative censoring. Nearly all statistical methods for censored data assume that censoring is noninformative. Topics considered within this class include: the relationships between three models for noninformative censoring, the use of likelihood methods for inferences about the distribution of survival time, the effects of censoring on the K-sample problem, and the effects of censoring on model testing. Also considered are several topics which relate to informative censoring models. These include: problems of nonidentifiability that can be encountered when attempting to assess a set of data for the type of censoring in effect, the consequences of falsely assuming that censoring is noninformative, and classes of informative censoring models.     

A comparison of methods for estimating plant population size

Assessing local population size is one of the most common tasks in biodiversity monitoring. Population size estimates are not only important for conservation management and population threat assessment; they also enter many other analyses in landscape ecology and conservation. It is therefore concerning that methods for estimating plant population sizes are not standardized. We surveyed the literature and found that the most commonly used methods are counting either all or only flowering individuals on a site, as well as counting individuals in random plots or plots on transects. Sometimes, these methods are combined in the same study, without assurance that they produce comparable results. We therefore conducted a field study, in which we obtained population size estimates from all four methods for six different calcareous grassland species at 18 study sites. Our results demonstrate not only substantial differences between overall count rates generated by the different methods, but methods that surveyed the whole population also systematically yielded lower counts when species were less visible and when the area was larger, suggesting that these methods suffer from biases that could distort species and site comparisons. We conclude that estimates from different methods should not be mixed, and that plot or transect based surveys have likely smaller biases for large areas or poorly visible individuals, and are therefore preferable.     

Semiparametric analysis of survival data with left truncation and dependent right censoring

Studies of chronic life-threatening diseases often involve both mortality and morbidity. In observational studies, the data may also be subject to administrative left truncation and right censoring. Because mortality and morbidity may be correlated and mortality may censor morbidity, the Lynden-Bell estimator for left-truncated and right-censored data may be biased for estimating the marginal survival function of the non-terminal event. We propose a semiparametric estimator for this survival function based on a joint model for the two time-to-event variables, which utilizes the gamma frailty specification in the region of the observable data. First, we develop a novel estimator for the gamma frailty parameter under left truncation. Using this estimator, we then derive a closed-form estimator for the marginal distribution of the non-terminal event. The large sample properties of the estimators are established via asymptotic theory. The methodology performs well with moderate sample sizes, both in simulations and in an analysis of data from a diabetes registry.     

A comparison of several published methods for barley anther culture

A number of methods have been published for barley (Hordeum vulgare L.) anther culture and have gained acceptance in different laboratories. The breeder's requirement is for a compromise method that gives good, repeatable results for a wide range of genotypes. Yet the routine production of spontaneously doubled haploid green regenerants remains difficult. Despite attempts to formulate a widely-applicable anther culture method, the 4 main published methods, compared here with one modified procedure, are quite distinct for a number of important characteristics. The methods interacted strongly with the 3 genotypes, and response ranged from zero to 28 green regenerants per 100 anthers plated. The current methods still require often substantial modification to suit local situations in order that the technology may be exploited by barley breeders.Abbreviations BAP benzylaminopurine - DH doubled haploid - FV final volume - IAA indoleacetic acid - IBA indole-3-butyric acid - MS Murashige & Skoog - PABA para-aminobenzoic acid     

A comparison of different methods for estimating single-trial P300 latencies

Inferences from comparative analyses of reaction time and P300 latency are stronger when the various aspects of the distribution across trials are treated in the same way for both variables. To this end, a number of studies have resorted to estimation of P300 latency at the single-trial level. This report presents a comparative evaluation of two common methods for such single-trial analysis, i.e., peak-picking and template-matching. Both methods were applied to a representative set of real data, comprising different task conditions and two age groups. Relevant scoring parameters were varied: low-pass filter settings (down to 0.94 Hz) for peak-picking, template duration (250–970 msec) and use of covariance vs. correlation for template-matching, and use of a noise-range criterion for both methods. It is concluded that peak-picking with a 3.4 Hz filter, and template-matching using covariance and template duration between 600 and 800 msec, are best in terms of sensitivity and reliability, with peak-picking surpassing template-matching. Also, the marked increase in the number of rejected trials when the noise-range criterion was applied resulted in unwanted modulation of behavioral effects of task conditions and age groups.     

Fast approximations of pseudo-observations in the context of right censoring and interval censoring

In the context of right-censored and interval-censored data, we develop asymptotic formulas to compute pseudo-observations for the survival function and the restricted mean survival time (RMST). These formulas are based on the original estimators and do not involve computation of the jackknife estimators. For right-censored data, Von Mises expansions of the Kaplan–Meier estimator are used to derive the pseudo-observations. For interval-censored data, a general class of parametric models for the survival function is studied. An asymptotic representation of the pseudo-observations is derived involving the Hessian matrix and the score vector. Theoretical results that justify the use of pseudo-observations in regression are also derived. The formula is illustrated on the piecewise-constant-hazard model for the RMST. The proposed approximations are extremely accurate, even for small sample sizes, as illustrated by Monte Carlo simulations and real data. We also study the gain in terms of computation time, as compared to the original jackknife method, which can be substantial for a large dataset.