Test-retest reliability of isometric mid-thigh pull maximum strength assessment: a systematic review

The aim of this systematic review was to explore the test-retest reliability of isometric mid-thigh pull maximum strength assessment. We searched through five databases to find studies that examined the test-retest reliability of peak force in the isometric mid-thigh pull exercise. From each included study, we extracted intra-class correlation coefficients (ICC) and/or coefficient of variation (CV). The methodological quality of the included studies was evaluated using the COSMIN checklist. A total of 16 good-to-excellent quality studies were included in the review. When considering results from all included studies, ICCs ranged from 0.73 to 0.99 (median ICC = 0.96), where 78% of ICCs were ≥ 0.90, and 98% of ICCs were ≥ 0.75. The range of reported CVs was from 0.7% to 11.1% (median CV = 4.9%), where 58% of CVs were ≤ 5%. Reliability was also good-to-excellent for both relative and absolute peak force and for both bilateral and unilateral isometric mid-thigh pull tests. The majority of studies did not find significant differences between testing sessions. It can be concluded that the isometric mid-thigh pull maximum strength assessment has good-to-excellent test-retest reliability. The isometric mid-thigh pull maximum strength assessment can be used as a reliable test in sports practice and for research purposes.     

Ultrasound does not provide reliable results for the measurement of the patellar tendon cross sectional area

PurposeThis study examined the reliability of patellar tendon cross sectional area (CSA) measurement using brightness mode ultrasonography.MethodsThe patellar tendon CSA of fourteen participants was examined on two different days and at three different positions (proximal, median and distal). Five trials per day were conducted in each position, replacing the ultrasound probe on every trial. The images were examined by three different and equally experienced observers. We compared the mean of the five trials in each position to examine the day, observer and position effect. Further, Bland and Altman plots, root mean square (RMS) differences and intraclass correlation coefficients (ICC) were calculated.ResultsThere was a significant (p < 0.05) day, observer and position effect on the CSA, while the average ICC was 0.592. The Bland and Altman plots showed that differences between conditions or groups, should be in average lower than 37% or higher than 55% of the patellar tendon CSA to be important for clinical or intervention studies.ConclusionOur findings show low reliability of the method, which resulted from the low clarity and unclear visibility of tissue boundaries in the ultrasound images. Therefore, the measurement of the CSA of the patellar tendon using ultrasound does not provide accurate and reliable results.     

Efficiency considerations in the analysis of inter-observer agreement

The reliability of binary assessments is often measured by the proportion of agreement above chance, as estimated by the kappa statistic. In this paper, we develop a model to estimate inter-rater and intra-rater reliability when each of the two observers has the opportunity to obtain a pair of replicate measurements on each subject. The model is analogous to the nested beta-binomial model proposed by Rosner (1989, 1992). We show that the gain in precision obtained from increasing the number of measurements per rater from one to two may allow fewer subjects to be included in the study with no net loss in efficiency for estimating the inter-rater reliability.     

Issues of cost and efficiency in the design of reliability studies

Reliability of continuous and dichotomous responses is usually assessed by means of the intraclass correlation coefficient (ICC). We derive the optimal allocation of the number of subjects k and the number of repeated measurements n that minimize the variance of the estimated ICC. Cost constraints are discussed for the case of normally distributed responses. Tables showing optimal choices of k and n are given, along with guidelines for the design of reliability studies in light of our results and those reported by others.     

On the Use of the Upper Confidence Limit for the Variance from a Pilot Sample for Sample Size Determination

In a recent paper, Browne (1995) investigated the use of a pilot sample for sample size calculation. Monte Carlo simulations indicated that using a 100 · (1 — γ) per cent upper one-sided confidence limit on the population varíance σ² leads to a sample size that guarantees the planned power with a probability of at least 1 ? γ. The purpose of this paper is to get further insight into the results of Browne by analytical considerations. Furthermore, the expected power is investigated when applying the strategy and recommendations for the choice of the pilot sample size are given.     

Power analysis to determine sample size for monitoring vegetation change in salt marsh habitats

Numerous initiatives are underway throughout New England and elsewhere to quantify salt marsh vegetation change, mostly in response to habitat restoration, sea level rise, and nutrient enrichment. To detect temporal changes in vegetation at a marsh or to compare vegetation among different marshes with a degree of statistical certainty an adequate sample size is required. Based on sampling 1 m² vegetation plots from 11 New England salt marsh data sets, we conducted a power analysis to determine the minimum number of samples that were necessary to detect change between vegetation communities. Statistical power was determined for sample sizes of 5, 10, 15, and 20 vegetation plots at an alpha level of 0.05. Detection of subtle differences between vegetation data sets (e.g., comparing vegetation in the same marsh over two consecutive years) can be accomplished using a sample size of 20 plots with a reasonable probability of detecting a difference when one truly exists. With a lower sample size, and thus lower power, there is an increased probability of not detecting a difference when one exists (e.g., Type II error). However, if investigators expect to detect major changes in vegetation (e.g., such as those between an un-impacted and a highly impacted marsh) then a sample size of 5, 10, or 15 plots may be appropriate while still maintaining adequate power. Due to the relative ease of collecting vegetation data, we suggest a minimum sample size of 20 randomly located 1 m² plots when developing monitoring designs to detect vegetation community change of salt marshes. The sample size of 20 plots per New England salt marsh is appropriate regardless of marsh size or permanency (permanent or non-permanent) of the plots.     

Efficient Bayesian Sample Size Calculation for Designing a Clinical Trial with Multi‐Cluster Outcome Data

Health care utilization and outcome studies call for hierarchical approaches. The objectives were to predict major complications following percutaneous coronary interventions by health providers, and to compare Bayesian and non‐Bayesian sample size calculation methods. The hierarchical data structure consisted of: (1) Strata: PGY4, PGY7, and physician assistant as providers with varied experiences; (2) Clusters: k_s providers per stratum; (3) Individuals: n_s patients reviewed by each provider. The main outcome event illustrated was mortality modeled by a Bayesian beta‐binomial model. Pilot information and assumptions were utilized to elicit beta prior distributions. Sample size calculations were based on the approximated average length, fixed at 1%, of 95% posterior intervals of the mean event rate parameter. Necessary sample sizes by both non‐Bayesian and Bayesian methods were compared. We demonstrated that the developed Bayesian methods can be efficient and may require fewer subjects to satisfy the same length criterion.     

A Bootstrap Procedure for Adaptive Selection of the Test Statistic in Flexible Two‐Stage Designs

Adaptive two‐stage designs allow a data‐driven change of design characteristics during the ongoing trial. One of the available options is an adaptive choice of the test statistic for the second stage of the trial based on the results of the interim analysis. Since there is often only a vague knowledge of the distribution shape of the primary endpoint in the planning phase of a study, a change of the test statistic may then be considered if the data indicate that the assumptions underlying the initial choice of the test are not correct. Collings and Hamilton proposed a bootstrap method for the estimation of the power of the two‐sample Wilcoxon test for shift alternatives. We use this approach for the selection of the test statistic. By means of a simulation study, we show that the gain in terms of power may be considerable when the initial assumption about the underlying distribution was wrong, whereas the loss is relatively small when in the first instance the optimal test statistic was chosen. The results also hold true for comparison with a one‐stage design. Application of the method is illustrated by a clinical trial example.     

Modification of the Computational Procedure in Parker and Bregman's Method of Calculating Sample Size from Matched Case–Control Studies with a Dichotomous Exposure

Summary .   Several authors have addressed the problem of calculating sample size for a matched case–control study with a dichotomous exposure. The approach of Parker and Bregman (1986, Biometrics 42, 919–926) is, in our view, one of the most satisfactory, since it requires specification of quantities that are often easily available to the investigator. However, its recommended implementation involves a computational approximation. We show here that the approximation performs poorly in extreme situations and can be easily replaced with a more exact calculation.     

Validity and reliability of 3D marker based scapular motion analysis: A systematic review

Methods based on cutaneous markers are the most popular for the recording of three dimensional scapular motion analysis. Numerous methods have been evaluated, each showing different levels of accuracy and reliability. The aim of this review was to report the metrological properties of 3D scapular kinematic measurements using cutaneous markers and to make recommendations based on metrological evidence.     

A sample size adjustment procedure for clinical trials based on conditional power

When designing clinical trials, researchers often encounter the uncertainty in the treatment effect or variability assumptions. Hence the sample size calculation at the planning stage of a clinical trial may also be questionable. Adjustment of the sample size during the mid-course of a clinical trial has become a popular strategy lately. In this paper we propose a procedure for calculating additional sample size needed based on conditional power, and adjusting the final-stage critical value to protect the overall type-I error rate. Compared to other previous procedures, the proposed procedure uses the definition of the conditional type-I error directly without appealing to an extra special function for it. It has better flexibility in setting up interim decision rules and the final-stage test is a likelihood ratio test.     

Foot pressure measurement: A review of methodology

Measurement of the distribution of the vertical reaction between the sole of the foot and its supporting surface, the foot-ground pressure pattern, has exercised the ingenuity of designers for the last century. Methods of making such measurements are presented with discussion of their various advantages for particular applications. Some applications of the results to further the understanding of normal and pathological conditions are noted.     

Conditional analysis of mixed Poisson processes with baseline counts: implications for trial design and analysis

The design of clinical trials is typically based on marginal comparisons of a primary response under two or more treatments. The considerable gains in efficiency afforded by models conditional on one or more baseline responses has been extensively studied for Gaussian models. The purpose of this article is to present methods for the design and analysis of clinical trials in which the response is a count or a point process, and a corresponding baseline count is available prior to randomization. The methods are based on a conditional negative binomial model for the response given the baseline count and can be used to examine the effect of introducing selection criteria on power and sample size requirements. We show that designs based on this approach are more efficient than those proposed by McMahon et al. (1994).     

Evaluation of Noether's Method of Sample Size Determination for the Wilcoxon-Mann-Whitney Test

NOETHER (1987) proposed a method of sample size determination for the Wilcoxon-Mann-Whitney test. To obtain a sample size formula, he restricted himself to alternatives that differ only slightly from the null hypothesis, so that the unknown variance o² of the Mann-Whitney statistic can be approximated by the known variance under the null hypothesis which depends only on n. This fact is frequently forgotten in statistical practice. In this paper, we compare Noether's large sample solution against an alternative approach based on upper bounds of σ² which is valid for any alternatives. This comparison shows that Noether's approximation is sufficiently reliable with small and large deviations from the null hypothesis.     

Detection of Cyclic Trends in Incidence Data Using the Efficiency Score Method

In studies involving a cyclic regularity, researchers usually have a good working knowledge regarding the peak time in the cycle. Capitalizing on this information, we derive the asymptotically uniformly most powerful unbiased test for detecting a cyclic trend using the likelihood score, and present the asymptotic power function of the test and the approximate formula for sample size. Numerical studies demonstrate great advantages of the proposed test over the standard test in terms of power and sample size. Asymptotic power of the score test is satisfactorily close to actual power. We also generalize this method so that it is applicable for incidence data from unequally spaced intervals or risk populations of unequal size.     

A Test of the Equivalence of Four Random Number Generators – A Simulation Study

Four pseudo random number generators were tested for equivalence. Using two different seed values for each generator, the robustness of a one-sample t-statistic was assessed under a stationary auto-regressive process. The degree of autocorrelation, sample size and significance level were varied for the eight sets of random numbers generated. Results showed an interaction effect between random number generator and alpha level of the t-distribution, suggesting that simulation results could depend on the random number generator selected.     

城市代谢研究评述:内涵与方法

随着城市发展面临的生态问题日益显著,部分研究者试图通过对自然生态系统进行类比来寻求解决途径,城市代谢理论应运而生。当以系统科学来研究城市生态系统时,哲学思想的引入为探索和城市及城市代谢的内涵提供了最原始的桥梁。因此,在介绍城市代谢内涵与研究进展的基础上,融合产业、家庭、社会等多尺度代谢理论,对城市代谢的边界进行扩展,将其分为狭义与广义两类,结合亚里士多德的"四因说"对其质料因(组分)、形式因(结构)、动力因(驱动力)和目的因(功能)进行识别分析,据此将城市代谢研究方法归纳为质料、形式和混合研究方法三类,并提出未来研究的主要动向和解决手段。城市代谢"四因图"可为相关研究者提供参考。     

Measuring voluntary quadriceps activation: Effect of visual feedback and stimulus delivery

Introduction: Quadriceps voluntary activation, assessed via the superimposed burst technique, has been extensively studied in a variety of populations as a measure of quadriceps function. However, a variety of stimulus delivery techniques have been employed, which may influence the level of voluntary activation as calculated via the central activation ratio (CAR). The purpose was to determine the effect of visual feedback, stimulus delivery, and perceived discomfort on maximal voluntary isometric contraction (MVIC) peak torque and the CAR. Methods: Quadriceps CAR was assessed in 14 individuals on two days using three stimulus delivery methods; (1) manual without visual feedback, (2) manual with visual feedback, and (3) automated with visual feedback. Results: MVIC peak torque and the CAR were not different between the automated with visual feedback (MVIC = 3.25, SE = 0.14 N m/kg; CAR = 88.63, SE = 1.75%) and manual with visual feedback (MVIC = 3.26, SE = 0.13 N m/kg, P = 0.859; CAR = 89.06, SE = 1.70%, P = 0.39) stimulus delivery methods. MVIC (2.99, SE = 0.12 N m/kg) and CAR (85.32, SE = 2.10%) were significantly lower using manual without visual feedback compared to manual with visual feedback and automated with visual feedback (CAR P < 0.001; MVIC P < 0.001). Perceived discomfort was lower in the second session (P < 0.05). Conclusion: Utilizing visual feedback ensures participant MVIC, and may provide a more accurate assessment of quadriceps voluntary activation.     

Modification of sample size in group sequential clinical trials

In group sequential clinical trials, sample size reestimation can be a complicated issue when it allows for change of sample size to be influenced by an observed sample path. Our simulation studies show that increasing sample size based on an interim estimate of the treatment difference can substantially inflate the probability of type I error in most practical situations. A new group sequential test procedure is developed by modifying the weights used in the traditional repeated significance two-sample mean test. The new test has the type I error probability preserved at the target level and can provide a substantial gain in power with the increase of sample size. Generalization of the new procedure is discussed.