Accuracy of sequential sampling plans based on Wald's sequential probability ratio test

Fowler, Gary W.

doi:10.1139/x83-158

Cited by 9 publications

(14 citation statements)

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“…density has exceeded a critical threshold associated with epidemic transmission. The statistical properties, assumptions, and errors associated with this method have been well documented (Wald 1947, Fowler 1983, Fowler and Lynch 1987b and it has been applied previously to mosquito control (Mackey and Hoy 1978).…”

Section: Methodsmentioning

confidence: 99%

“…Intermediate between these two levels, larger sample sizes are required to reach a conclusion. It should be noted that the functions for the operating characteristic curve and expected average number of houses are only approximate because of overshooting the threshold when decisions are made (Fowler 1983). The result of overshooting is that actual values for ␣ and ␤ are less than those chosen to construct the sampling plan, whereas the number of houses needed in the Þeld to reach a terminating decision may be more than that indicated by WaldÕs average sample number function.…”

Section: Figmentioning

confidence: 99%

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Early Warning of Malaria Epidemics in African Highlands Using <I>Anopheles</I> (Diptera: Culicidae) Indoor Resting Density

Lindblade¹,

Walker

Wilson³

2000

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Several highland regions of Africa recently have suffered malaria epidemics. Because malaria transmission is unstable and the population has little or no immunity, these highlands are prone to explosive outbreaks when densities of Anopheles exceed critical levels and conditions favor transmission. If an incipient epidemic can be detected early enough, control efforts may reduce morbidity, mortality, and transmission. Here we present three methods (direct, minimum sample size, and sequential sampling approaches) that could be used to determine whether the household indoor resting density of Anopheles gambiae s.I. has exceeded critical levels associated with epidemic transmission. Data on Anopheles density before, during, and after a malaria epidemic (December 1997-July 1998) in the highlands of southwestern Uganda were evaluated to demonstrate the application of these three approaches. During this epidemic, a density of 0.25 Anopheles mosquitoes per house was associated with epidemic transmission, whereas 0.05 mosquitoes per house was chosen as a normal level expected during nonepidemic months. The direct approach to calculating mean Anopheles density with an allowable error of 20-50% of the mean would require the sampling of 102-16 houses, respectively. In contrast, with only seven houses, the minimum sample size approach could be used to determine whether Anopheles density had exceeded the critical level. This method, however, would result in an overestimation of the risk of an epidemic at low Anopheles density. Finally, a sequential sampling plan could require as many as 50 houses to conclude that risk of an epidemic existed, but this disadvantage is offset by the ability to preset the probabilities of concluding that risk of an epidemic exists at both the critical and normal Anopheles densities. Our study illustrated that it is feasible, and probably expedient, to include monitoring of Anopheles density in highland malaria epidemic early warning systems.

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Section: Methodsmentioning

confidence: 99%

Section: Figmentioning

confidence: 99%

Early Warning of Malaria Epidemics in African Highlands Using <I>Anopheles</I> (Diptera: Culicidae) Indoor Resting Density

Lindblade¹,

Walker

Wilson³

2000

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“…Alternatively, once a decision has been made using a division of multiple categories, and sample examination ceased, iterations could be undertaken using already collected count data as in the present study to achieve a modal abundance rank (i.e., in a sense, a simplified form of bootstrapping). Similarly, Fowler (1983) used Monte Carlo simulations to reduce the number of samples needed in field surveys.…”

Section: Sequential Samplingmentioning

confidence: 99%

Use of sequential sampling of amphipod abundance to classify the biotic integrity of acid-sensitive lakes

France¹

1992

Environmental Management

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/ A sequential sampling program using previously published zoobenthos data is described for ubiquitous, costeffective biomonitoring of the effects of lake acidification.Spring densities of the littoral amphipod Hyalella azteca are quantitatively sorted into five abundance catagories. An essential step in the a priori definition of decision criteria is the stratification of proportional densities per unit macrophyte biomass in relation to aqueous total phosphorus concentrations. Density rankings were related to lake acidity and to detailed lake-specific information on patterns of Hyalella life history and acid tolerance. Incorporation of Hyalella abundance as a potential metric for the assessment of the biological integrity of acid-sensitive waters is recommended. The temporal integration of transient changes in spring meltwater chemistry is an important rationale for the development of such biomonitoring procedures.Environmental scientists greatly err in assuming that measures of aqueous chemical imbalance alone are sufficient to gauge ecosystem stress (Karr 1987). Living organisms provide convenient full-time monitors of transient variability in environmental quality, an important consideration when assessing the effects of anthropogenic acidification on lakes and rivers in north-temperate climates. Because the soil in such regions may still be partially frozen in the spring, much of the acidic snowmelt can run off quickly with little neutralization taking place within the watershed. For example, typically between 36% and 77% of the annual export of H + from watersheds over much of central Ontario occurs during this short interval (Jeffries and others 1979). Due to logistic difficulties, acidic pulses are rarely monitored throughout the littoral zone over the melting period. More frequently, if the spring episodes are sampled at all, they are normally estimated from midlake stations or inferred from the more accessible outflows, which are assumed representative of the lake as a whole. Such measures are at best, however, an imprecise reflection of the actual environment to which littoral organisms are exposed, and misleading conclusions regarding the severity of such pulses can arise (France and LaZerte 1987). Obviously, the function of biomon-

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“…For example, the Statistical Research Group (1946) reported that as little as 400Jo of the samples normally needed in fixed sample size inventories were needed for a sequential sampling inventory to make an appropriate decision. Fowler (1988) similarly stated that only 40-60 per cent as many observations are required in sequential sampling as in an equally reliable fixed sample size procedure. Sequential sampling has been primarily used in forestry for ·deciding whether insect infestations have reached sufficient intensity to justify control (e.g.…”

Section: Introductionmentioning

confidence: 99%

Sequential sampling and modelling for mean dominant height estimation

Brack

Marshall

1990

Australian Forestry

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A method of checking the validity of model predictions of the mean dominant height {MDH) for a cutting unit using sequential sampling is presented. Inventory data provided by the New South Wales Forestry Commission were used to test the impact of decision criteria and acceptable type I and type 2 error levels on average sample size. Using sequential sampling to check model predictions of cutting unit MDH lowered the standard error of the prediction and reduced the maximum error by over half that of the using model predictions alone. The average sample size for the model with sequential sampling varied with the decision criteria and acceptable error levels. Using sequential sampling to check the validity of model predictions can reduce the number of heights that need to be measured during an inventory without greatly increasing the error in estimating MDH for a cutting unit.

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Accuracy of sequential sampling plans based on Wald's sequential probability ratio test

Cited by 9 publications

References 0 publications

Early Warning of Malaria Epidemics in African Highlands Using <I>Anopheles</I> (Diptera: Culicidae) Indoor Resting Density

Early Warning of Malaria Epidemics in African Highlands Using <I>Anopheles</I> (Diptera: Culicidae) Indoor Resting Density

Use of sequential sampling of amphipod abundance to classify the biotic integrity of acid-sensitive lakes

Sequential sampling and modelling for mean dominant height estimation

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