Teacher’s Corner: The One-Sample Runs Test: A Category of Exception

1994 ◽  
Vol 19 (3) ◽  
pp. 296-303 ◽  
Author(s):  
Robert G. Mogull
Keyword(s):  
Sample Size ◽  
Power Of The Test ◽  
Overall Performance ◽  
The One ◽  
Run Lengths ◽  
Nonrandom Pattern

The popular One-Sample Runs Test is used to identify a nonrandom pattern in a sequence of dichotomous elements. Although the test is generally effective in the identification of patterns, it is demonstrated to be incapable of signaling departures from randomness with run lengths of two. Further-more, with run lengths of two, increasing the sample size reduces the power of the test. Run lengths strictly of two, therefore, generate a unique category of anomaly in the test’s overall performance.

scholarly journals Importance of Inoculum Size and Sampling Effect in Rapid Antigen Detection for Diagnosis of Streptococcus pyogenes Pharyngitis

2000 ◽  
Vol 38 (1) ◽  
pp. 279-281 ◽  
Author(s):  
Bradley Kurtz ◽  
Michael Kurtz ◽  
Martha Roe ◽  
James Todd
Keyword(s):  
Sample Size ◽  
Streptococcus Pyogenes ◽  
Disease Status ◽  
Inoculum Size ◽  
Antigen Detection ◽  
Detection Rates ◽  
Sample Distribution ◽  
Antigen Tests ◽  
The One ◽  
Antigen Testing

ABSTRACT Current recommendations suggest that negative rapid Streptococcus pyogenes antigen tests be backed up with a culture, reflecting evidence that culture may have a higher sensitivity and also that testing of a second swab may yield a different (i.e., a positive) result because of variation in sample size or distribution. If the latter is common, the sensitivities of current antigen detection tests might be improved by simply increasing the amount of sample tested. The present study assessed the effect of antigen testing of two swabs extracted together compared to independent testing of each swab extracted separately for children with clinical pharyngitis. S. pyogenes grew from one or both swabs for 198 (37%) of 537 children. The combined culture was significantly ( P < 0.05) more sensitive than culture of either swab alone. Compared to combined culture, antigen testing of two swabs extracted and tested together was significantly more sensitive than two single swab extractions (94.1 versus 80%; P = 0.03); however, the specificity was decreased (81.5 versus 89.8 to 92.7%; P < 0.05). This study suggests that sample size and/or uneven sample distribution may have influenced the apparent sensitivities of prior studies that compared antigen tests to a single plate culture. A strategy, such as the one used in the present study, that increases the sample size available for antigen testing (i.e., extraction of samples from both swabs) may improve detection rates to a level that will better approximate true disease status and obviate the need for backup cultures if specificity can be improved.

How Large Should the Sample Be? Part II—The One-Sample Case for Survey Research

1985 ◽  
Vol 45 (2) ◽  
pp. 271-280 ◽  
Author(s):  
Dennis E. Hinkle ◽  
J. Dale Oliver ◽  
Charles A. Hinkle
Keyword(s):  
Sample Size ◽  
Survey Research ◽  
Effect Size ◽  
Previous Article ◽  
Type Ii ◽  
Type Ii Error ◽  
The One ◽  
Sample Case

In a previous article, the authors discuss the importance of the effect size and the Type II error as factors in determining the sample size (Hinkle and Oliver, 1983). Tables were developed and presented for one-factor designs with k levels (2 ≤ k ≤ 8). However, between the time the article was submitted and its publication, the authors presented these tables at several national and regional meetings. A recurring question from colleagues attending these meetings was how these tables could be used for the one-sample case ( k = 1). Since they could not be, we were encouraged to develop comparable tables for the one-sample case. Thus, the purpose of this paper is to readdress the sample size question and to present these tables.

Randomized Sample Size F Tests for the One-Way Layout

2010 ◽  
Author(s):  
João T. Mexia ◽  
Elsa E. Moreira ◽  
Theodore E. Simos ◽  
George Psihoyios ◽  
Ch. Tsitouras
Keyword(s):  
Sample Size ◽  
The One

Stopping Performance in Familiar and Unfamiliar Vehicles

1987 ◽  
Vol 31 (7) ◽  
pp. 762-765
Author(s):  
Thomas A. Ranney ◽  
Nathaniel H. Pulling
Keyword(s):  
Motor Vehicle ◽  
Reaction Times ◽  
Driving Performance ◽  
Driving Simulators ◽  
Vehicle Accidents ◽  
Approach Speed ◽  
Overall Performance ◽  
Driving Range ◽  
The One ◽  
Performance Research

Lack of vehicle familiarity is a contributing factor in motor-vehicle accidents. It may also contaminate results in experiments where subjects are required to drive unfamiliar vehicles or driving simulators. An instrumented driving range, including a signalized intersection, was developed to evaluate driving performance in subjects' own vehicles. Fourteen drivers completed approximately fifty laps of the one-half mile closed course in their own vehicles and in an unfamiliar passenger van. Their task was to stop at the stopline following the change of the traffic signal from green to yellow. Brake reaction time, smoothness of deceleration, approach speed, and stopping accuracy were recorded. In the unfamiliar van, brake reaction times were faster and drivers were more likely to stop considerably before the stop line than in their own vehicle. Deceleration was slightly smoother in the unfamiliar van. Individual differences in approach speed were stronger than differences associated with vehicles. Overall performance was influenced more by the position of the vehicle at yellow onset than by vehicle familiarity. Results were interpreted as suggesting heightened driver awareness in the unfamiliar vehicle. Implications for the safety of drivers in unfamiliar vehicles are discussed. The use of unfamiliar vehicles in driving performance research and problems of data analysis resulting from the use of drivers in their own vehicles are also discussed.

scholarly journals Using Bootstrap Method to Evaluate the Power of Tests for Non-Linearity in Asymmetric Price Relationship

2013 ◽  
Vol 5 (4) ◽  
pp. 237-241
Author(s):  
Henry De-Graft Acquah
Keyword(s):  
Sample Size ◽  
Bootstrap Method ◽  
Complex Model ◽  
Model Complexity ◽  
Bootstrap Sample ◽  
Power Of The Test ◽  
Data Generating Process ◽  
Price Relationship ◽  
False Null Hypothesis ◽  
The Bootstrap Method

This paper introduces and applies the bootstrap method to compare the power of the test for asymmetry in the Granger and Lee (1989) and Von Cramon-Taubadel and Loy (1996) models. The results of the bootstrap simulations indicate that the power of the test for asymmetry depends on various conditions such as the bootstrap sample size, model complexity, difference in adjustment speeds and the amount of noise in the data generating process used in the application. The true model achieves greater power when compared with the complex model. With small bootstrap sample size or large noise, both models display low power in rejecting the (false) null hypothesis of symmetry.

scholarly journals Choosing the Target Difference (“effect size”) for a Randomised Controlled Trial - DELTA2 Guidance

2018 ◽  
Author(s):  
Jonathan A. Cook ◽  
Steven A. Julious ◽  
William Sones ◽  
Lisa V. Hampson ◽  
Catherine Hewitt ◽  
...  
Keyword(s):  
Randomised Controlled Trial ◽  
Sample Size ◽  
Controlled Trial ◽  
Sample Size Calculation ◽  
Main Body ◽  
Target Difference ◽  
Superiority Trial ◽  
The Difference ◽  
The One ◽  
Randomised Controlled

The aim of this document is to provide practical guidance on the choice of target difference used in the sample size calculation of a randomised controlled trial (RCT). Guidance is provided with a definitive trial, one that seeks to provide a useful answer, in mind and not those of a more exploratory nature. The term &ldquo;target difference&rdquo; is taken throughout to refer to the difference that is used in the sample size calculation (the one that the study formally &ldquo;targets&rdquo;). Please see the glossary for definitions and clarification with regards other relevant concepts. In order to address the specification of the target difference, it is appropriate, and to some degree necessary, to touch on related statistical aspects of conducting a sample size calculation. Generally the discussion of other aspects and more technical details is kept to a minimum, with more technical aspects covered in the appendices and referencing of relevant sources provided for further reading.The main body of this guidance assumes a standard RCT design is used; formally, this can be described as a two-arm parallel-group superiority trial. Most RCTs test for superiority of the interventions, that is, whether or not one of the interventions is superior to the other (See Box 1 for a formal definition of superiority, and of the two most common alternative approaches). Some common alternative trial designs are considered in Appendix 3. Additionally, it is assumed in the main body of the text that the conventional (Neyman-Pearson) approach to the sample size calculation of an RCT is being used. Other approaches (Bayesian, precision and value of information) are briefly considered in Appendix 2 with reference to the specification of the target difference.

scholarly journals Effect of Rotor Tip Clearance and Configuration on Overall Performance of a 12.77-Centimeter Tip Diameter Axial-Flow Turbine

1979 ◽  
Author(s):  
J. E. Haas ◽  
M. G. Kofskey
Keyword(s):  
Experimental Investigation ◽  
Rotor Blade ◽  
Axial Flow ◽  
Single Stage ◽  
Rotor Blades ◽  
Tip Clearance ◽  
Blade Height ◽  
Overall Performance ◽  
Flow Reaction ◽  
The One

An extensive experimental investigation was made to determine the effect of varying the rotor tip clearance of a 12.77-cm-tip diameter, single-stage, axial-flow reaction turbine. In this investigation, the rotor tip clearance was obtained by use of a recess in the casing above the rotor blades and also by use of a reduced blade height. For the recessed casing configuration, the optimum rotor blade height was found to be the one where the rotor tip diameter was equal to the stator tip diameter. The tip clearance loss associated with this optimum recessed casing configuration was less than that for the reduced blade height configuration.

scholarly journals Study of Indoor Small Cell Deployments

2021 ◽  
Author(s):  
Rui R. Paulo ◽  
Fernando J. Velez ◽  
Bahram Khan
Keyword(s):  
Packet Loss ◽  
Small Cell ◽  
Small Cells ◽  
Loss Ratio ◽  
Packet Loss Ratio ◽  
Overall Performance ◽  
The One ◽  
Performance Results ◽  
Effective Sinr

This work aims at studying the indoor deployment of small cells, also known as femtocells, to provide coverage to a 5×5 grid geometry. The number of deployed HeNBs is 4, 5, or 6. An updated version of LTE-Sim is considered to extract values for Exponential Effective SINR Mapping (EESM), Packet Loss Ratio (PLR), maximum number of supported users, goodput and delay. Results reveal that the use of four HeNBs corresponds to the highest values of EESM. For the considered geometry, 3GPP suggested a maximum of five HeNBs. However, this deployment shows worser performance compared to the topology with four HeNBs. The geometry with six HeNBs is the one with the best overall performance results for the 5×5 grid of apartments.

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