Resampling Simulation Research Articles

Binocular rivalry is slower in first-degree relatives of schizophrenics

Many individuals with schizophrenia experience a profound deficit in global cognitive ability, which is related to poor functional outcomes. Historically, the standard of assessing neurocognitive impairments is one of extensive neuropsychological batteries that are labour-intensive. The present study examined whether a brief neurocognitive assessment (BNA) instrument could effectively estimate global neurocognition and further examined its clinical utility.The validity and clinical utility of a BNA that takes approximately 10 min to administer was examined against a full neuropsychological battery that takes approximately 90 min to administer in a large and heterogeneous sample of 1303 patients with schizophrenia.The BNA explained 76% of the variance in global neurocognition in the total sample and remained consistent in subsamples stratified by clinical characteristics (e.g., severity of psychopathology) and in randomized re-sampling simulations. The two items that comprised the BNA were the letter-number sequencing test, a measure of working memory, and the digit-symbol test, a measure of processing speed. Next, perhaps more importantly, the BNA and full neuropsychological battery were related to symptoms and functional status to a similar degree in both univariate and multivariate regression models; moreover, both instruments were sensitive to longitudinal treatment related change to a similar degree.The BNA is able to rapidly, easily, and validly assess global neurocognition in schizophrenia. The BNA was associated with important clinical outcomes to a similar degree as a full cognitive battery. This tool provides clinicians and researchers a means to assess global neurocognitive impairments without requiring extensive neuropsychological testing.

Sequential Sampling Plans for Western Flower Thrips (Thysanoptera: Thripidae) on Greenhouse Cucumbers

The development of cost-effective and reliable sampling programs for the management of western flower thrips, Frankliniella occidentalis (Pergande), on greenhouse cucumbers is important for getting growers to adopt economic injury levels and economic thresholds. The objectives of this study were to develop two sequential sampling plans. A fixed-precision sequential sampling plan was designed for estimating F. occidentalis adult density at a fixed-precision level on cucumber flowers. Also, a sequential sampling plan for classifying thrips population levels as below or above economic thresholds was developed to assist in decision making for the timing of pesticide applications. Both sequential sampling plans were validated using a resampling simulation technique on nine independent data sets ranging in density from 1.25 to 12.95 adults per flower. With the fixed-precision sampling plan, average means obtained in 100 repeated simulation runs were within the 95% CI of the estimated mean for all data sets. Appropriate levels of precision for the different population densities were recommended based on the simulation results. With sequential sampling for classifying the population levels of thrips in terms of an economic threshold, it has the advantage of requiring smaller sample sizes to determine the population status when the population densities differ greatly from the critical density (i.e., economic threshold). However, this plan needs a great number of samples when population density is close to the critical density. In this case, use of a combination of both sampling plans is recommended.

Bootstrapping: As easy as 1-2-3

The bootstrap is a powerful non-parametric statistical technique for making probability-based inferences about a population parameter. Through a Monte-Carlo resampling simulation, bootstrapping empirically generates a statistic's entire distribution. From this simulated distribution, inferences can be made about a population parameter. Assumptions about normality are not required. In general, despite its power, bootstrapping has been used relatively infrequently in social science research, and this is particularly true for business research. This under-utilization is likely due to a combination of a general lack of understanding of the bootstrap technique and the difficulty with which it has traditionally been implemented. Researchers in the various fields of business should be familiar with this powerful statistical technique. The purpose of this paper is to explain how this technique works using Lotus 1-2-3, a software package with which business people are very familiar.

Spatial distribution and sampling plans for Thrips palmi (Thysanoptera: Thripidae) infesting fall potato in Korea.

The spatial distribution of adult and immature Thrips palmi Karny on fall potato, Solanum tuberosum L., on Cheju Island, Korea, was studied over a 2-yr period by visually inspecting potato leaves. The majority of thrips collected from the leaves were observed in the top one-third of the plant. The within-field spatial patterns of adults and immature thrips were aggregated. The slopes and intercepts of Taylor's power law did not differ among adults and immature thrips. A fixed-precision-level sampling plan was developed using the parameters from Taylor's power law and was tested with resampling simulations using eight independent data sets. Over a wide range of densities, the simulation demonstrated that actual sampling precision (d = SEM/mean) values at d = 0.25 averaged < 0.24 in all cases. A binomial sampling plan for estimating mean density was developed using an empirical model evaluated at tally thresholds (the minimum number of insects present before a leaf is considered infested) of one, three, five, and eight thrips per leaf. Increasing sampling size had little effect on the precision of the estimated mean regardless of tally threshold (T). However, increasing T had a dramatic effect on precision. The best tally threshold for estimating thrips density based on the applicable density ranges and the precision of the model was T = 5. A binomial sampling plan with a tally threshold of five and a fixed sample size of 30 leaves should be an effective replacement for enumerative counts when thrips average < 10 per leaf.

LIFE STAGE SIMULATION ANALYSIS: ESTIMATING VITAL-RATE EFFECTS ON POPULATION GROWTH FOR CONSERVATION

We developed a simulation method, known as life-stage simulation analysis (LSA) to measure potential effects of uncertainty and variation in vital rates on population growth (λ) for purposes of species conservation planning. Under LSA, we specify plausible or hypothesized levels of uncertainty, variation, and covariation in vital rates for a given population. We use these data under resampling simulations to establish random combinations of vital rates for a large number of matrix replicates and finally summarize results from the matrix replicates to estimate potential effects of each vital rate on λ in a probability-based context. Estimates of potential effects are based on a variety of summary statistics, such as frequency of replicates having the same vital rate of highest elasticity, difference in elasticity values calculated under simulated conditions vs. elasticities calculated using mean invariant vital rates, percentage of replicates having positive population growth, and variation in λ explained ...

DEVELOPMENT AND VALIDATION OF A FIXED-PRECISION SEQUENTIAL SAMPLING PLAN FOR ESTIMATING BROOD ADULT DENSITY OF DENDROCTONVS PSEUDOTSUGAE (COLEOPTERA: SCOLYTIDAE)

AbstractThe Douglas-fir beetle, Dendroctonus pseudotsugae Hopkins, attacks Douglas-fir, Pseudotsuga menziesii (Mirb.) Franco (Pinaceae), throughout western North America. Periodic outbreaks cause increased mortality of its host. Land managers and forest health specialists often need to determine population trends of this insect. Bark samples were obtained from 326 trees distributed over 21 stands during a 2-year period in late winter to early spring of 1997 and 1998 in the Colorado Front Range. The variance to mean relationship of brood adults was examined using the Taylor power law, and a fixed-precision sampling plan was developed using Green’s method. Stop lines and minimum number of samples required to estimate brood adult density per 0.046 m2 with precision levels of 0.1, 0.2, and 0.3 were calculated. A resampling simulation conducted with an independent data set indicated that desired precision levels were not met. Theoretical precision levels were adjusted until desired precision levels were achieved. Average number of samples needed to estimate brood adult densities up to 25.1 adults per 0.046 m2 with precision levels of 0.09, 0.2, and 0.3 were 91, 20, and 8, respectively. For densities greater than 25.1 brood adults per 0.046 m2, conservative estimates are obtained with 72, 15, and 6 samples for precision levels of 0.09, 0.2, and 0.3, respectively. An emergence ratio can be obtained by dividing the estimated density of brood adults by twice the number of gallery starts. This system provides the user with an immediate assessment of the population trend of Douglas-fir beetle. The data collected compare favorably with data from other Douglas-fir beetle outbreaks reported in the literature. The use of this plan outside the Colorado Front Range, or by sampling at a different height, should be cautioned until additional data from other locations and sampling heights are examined.

The influence of sampling interval on the accuracy of trail impact assessment

Trail impact assessment and monitoring (IA&M) programs have been growing in importance and application in recreation resource management at protected areas. This paper addresses a fundamental issue in designing trail IA&M surveys: the choice of sampling interval. Specifically, the influence of sampling interval on the accuracy of estimates for selected trail impact problems was examined using a resampling simulation method. A complete census of four impact-types on 70 backcountry trails in the Great Smoky Mountains National Park was utilized as the base dataset for the analyses. The census data were resampled at increasing intervals to create a series of simulated point datasets. At each sampling interval level, the accuracy of simulated datasets was evaluated by comparing the estimates of frequency of occurrence and lineal extent for each impact-type with actual census values. Simulation results indicate that increasing sampling intervals are associated with an overall increase in accuracy loss for all four impact-types. The direction of accuracy loss for lineal extent estimates is mixed, while frequency of occurrence estimates are consistently and substantially lower than the actual values. Responses of accuracy loss to increasing sampling intervals vary across impact-types on extent estimates, but are consistent on the frequency estimates. These findings suggest that systematic point sampling can be an appropriate method for estimating lineal extent but not the frequency of trail impacts. Sample intervals of less than 100 m appear to yield an excellent level of estimate accuracy for the four impact-types evaluated. The census-based trail survey and the resampling simulation method developed in this study can be a valuable first step in establishing long-term trail IA&M programs, in which an optimal sampling interval range with acceptable accuracy is determined before investing efforts in data collection.

Spatial Distribution of Thrips in Greenhouse Cucumber and Development of a Fixed-Precision Sampling Plan for Estimating Population Density

Dispersion patterns of phytophagous thrips (Thysanoptera: Thripidae) were determined for greenhouse cucumber, Cucumis sativus L., in Cheju-do, Korea, during 1995 and 1996. Thrips populations were sampled using leaf sample, yellow sticky trap and visual estimate concurrently on each sampling date. Frankliniella occidentalis (Pergande) was the most dominant thrips species, accounting 92% of all specimens collected from leaf samples and yellow sticky traps. Dispersion indices generated by Taylor's power law and Iwao's patchiness regression were compared. Generally, Taylor's power law provided better description of mean-variance relationship than did Iwao's patchiness regression with exception of the data from the sticky trap. Slopes and intercepts of Taylor's power law from leaf sample and visual estimate did not differ among thrips species and surveyed greenhouses. A fixed-precision-level of sequential sampling plan was developed using Taylor's power law parameters generated from total number of thrips in leaf sample and visual estimate. This sampling plan for visual estimate was tested with sequential resampling simulation using 4 independent data sets. Resampling simulation analysis demonstrated that actual D values were always less than desired D values of 0.20, 0.25 and 0.30.

Sequential Sampling of Brachycaudus helichrysi (Homoptera: Aphididae) in Sunflower Fields

A sequential sampling plan for the leaf-curling plum aphid, Brachycaudus helichrysi Kaltenbach, on sunflower was developed using the fixed-precision method of Green. Our sequential sampling plan was validated using a resampling simulation approach with 5 independent data sets ranging in density from 5.8 to 188.2 aphids per sample unit. Sampling plans with a relative precision level of 0.30 were not recommended because of the low sample number and high variation that invalidated the normality assumption. Simulated results did not agree with the desired precision level for only 1 data set. This data set also deviated from our Taylor power law model. For the other data sets, simulated precision levels were generally better than the desired fixed levels. Variability of the B. helichrysi sequential sampling criteria was high for mean estimates and for the levels of precision.

Spatial Distribution of Adult Bemisia tabaci (Homoptera: Aleyrodidae) in Cotton and Development and Validation of Fixed-Precision Sampling Plans for Estimating Population Density

We conducted studies to examine distributional patterns of adult Bemisia tabaci (Gennadius) strain B (also referred to as Bemisia argentifolii Bellows & Perring) in cotton, Gossypium hirsutum L. , and to develop and validate a sequential sampling plan for estimating population density. Adults were consistently more abundant on mainstem leaves from the top stratum of cotton plants than on mainstem leaves from the middle and bottom strata. Counts on mainstem leaves from the top of the plant also had the lowest relative variation. Adults on the top stratum of the plant were fairly uniformly distributed over leaves from mainstem nodes 2–7 (terminal = node 1), but numbers of adults were highest and least variable on fifth-node leaves. Patterns of aggregation, as measured by Taylor's power law, did not differ among the top, middle, and bottom strata of cotton plants and were similar among the first six mainstem leaves below the mainstem terminal. Ratios between counts of adults on individual leaves from the top stratum of the plant and whole plant counts were variable and averaged (± SD) 0.075 ± 0.071. Based on fifth mainstem node leaves as the sample unit, we used Kuno's and Green's methods to develop fixed–precision sequential sampling plans. The underlying mean-variance models for these methods and performance of the sequential stop lines were compared and evaluated using a resampling simulation of independent data sets with means ranging from 2 to 50 adults per leaf. Compared with lwao's mean crowding regression, Taylor's power law was a less biased predictor of variance. As a result, Green's plan, on average, achieved the desired precision better than Kuno's plan even though neither plan consistently gave mean estimates with the desired precision. Further simulations provided preliminary adjustments in the stop lines for field implementation.