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Results for “Statistical power analysis”

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PubMed1990

Self-reported neuroendocrine effects of antipsychotics in women: a pilot study.

Although neuroendocrine adverse effects (NAEs) of antipsychotic agents in women have been widely reported, it has been generally assumed that either (1) tolerance to these effects develops with chronic use, (2) patients adjust to the effects, or (3) a trial of dopamine-agonist treatment is effective. We have begun to examine the prevalence of chronic adverse effects and their effect on compliance using a pilot study of self-reported NAEs, antipsychotic drugs, and compliance patterns in a naturalistic setting. Twenty chronic psychiatric outpatients who had been continuously prescribed antipsychotic agents for a minimum of six months were interviewed. The major finding is the greater antipsychotic dose exposure among those with self-reported NAEs compared with those without NAEs (781 +/- 606 chlorpromazine-equivalent mg/d vs. 125 +/- 117, p less than 0.001). High-potency agents were prescribed for all of the patients reporting amenorrhea and/or galactorrhea, although the relationship between potency group (high vs. low) and total neuroendocrine effects was not significant. Self-reported compliance was not significantly related to neuroendocrine adverse effects. However, a trend toward the association of self-reported galactorrhea and noncompliance (p = 0.08) is noted. The implications of these findings and a suggested approach for their replication in a more powerful statistical analysis is discussed.

Adult↗
PubMed2001

The power of statistical tests in meta-analysis.

Calculations of the power of statistical tests are important in planning research studies (including meta-analyses) and in interpreting situations in which a result has not proven to be statistically significant. The authors describe procedures to compute statistical power of fixed- and random-effects tests of the mean effect size, tests for heterogeneity (or variation) of effect size parameters across studies, and tests for contrasts among effect sizes of different studies. Examples are given using 2 published meta-analyses. The examples illustrate that statistical power is not always high in meta-analysis.

Humans↗
PubMed1991

Postural sway of human infants while standing in light and dark.

Postural sway was measured in 12-14-month-old human infants and in adults while they were standing in the light and dark. Spectral density analyses conducted on all frequencies, at specific frequencies, and for individual subjects showed that infants generally did not sway significantly more in the dark than in the light, whereas adults did. For example, infants' dark/light sway proportions were 1.12 and 1.21 for the anterior-posterior and lateral dimensions, respectively, compared to adult values of 2.23 and 3.43 for one-footed stance, and 1.43 and 2.13 for two-footed stance. A statistical power analysis indicated that if the dark/light proportions for infants had been comparable to those for adults, significant differences could have been detected. These findings indicate that the early regulation of standing posture does not depend on the continuous availability of visual information.

Dark Adaptation↗
PubMed1984

[Can therapeutic trials serve as a model for the evaluation of diagnostic methods?].

Many health care professionals think that diagnostic technologies must be assessed as treatments are and that controlled diagnostic trials must be organized for evaluation of diagnostic tests. There are many differences between these two types of trials relating with: unfeasibility of blind judgments, biases due to requesting of diagnostic tests in addition to technologies to be compared, number of patients required for a sufficiently powerful statistical analysis, diverging interest of the various clinical teams involved into the assessment. A different approach using simulation methods and decision trees appears more appropriate in the evaluation of diagnostic technics.

Clinical Trials as Topic↗
PubMed1993

The effect of age on human corneal thickness. Statistical implications of power analysis.

The corneal thickness of 108 human subjects, ranging from 17 to 75 years of age, was measured using ultrasound pachometry. One central, four mid-peripheral and four peripheral corneal positions along the vertical and horizontal meridians were assessed using ultrasound pachometry. No significant differences were found in the thicknesses of the central, midperipheral or peripheral cornea with increasing age using analysis of variance. These results suggest that ageing has no significant effect on human corneal thickness between the ages of 16 to 75 years. However the high Type II error probability (beta = 0.90) suggests that 108 subjects (18 in each age group) were insufficient to adequately answer the question. Thus power analysis may help explain the conflicting reports available in literature. The diversity in data interpretation may be due to the statistically small sample sizes used in most studies. Power analysis shows that at least 80 subjects are needed in each age group (480 subjects in total) before a statistically reliable test of the null hypothesis is possible. This study emphasizes the importance of power analysis in calculating an adequate sample size.

Adolescent↗
PubMed2003

Automatic CTF correction for single particles based upon multivariate statistical analysis of individual power spectra.

Three-dimensional electron cryomicroscopy of randomly oriented single particles is a method that is suitable for the determination of three-dimensional structures of macromolecular complexes at molecular resolution. However, the electron-microscopical projection images are modulated by a contrast transfer function (CTF) that prevents the calculation of three-dimensional reconstructions of biological complexes at high resolution from uncorrected images. We describe here an automated method for the accurate determination and correction of the CTF parameters defocus, twofold astigmatism and amplitude-contrast proportion from single-particle images. At the same time, the method allows the frequency-dependent signal decrease (B factor) and the non-convoluted background signal to be estimated. The method involves the classification of the power spectra of single-particle images into groups with similar CTF parameters; this is done by multivariate statistical analysis (MSA) and hierarchically ascending classification (HAC). Averaging over several power spectra generates class averages with enhanced signal-to-noise ratios. The correct CTF parameters can be deduced from these class averages by applying an iterative correlation procedure with theoretical CTF functions; they are then used to correct the raw images. Furthermore, the method enables the tilt axis of the sample holder to be determined and allows the elimination of individual poor-quality images that show high drift or charging effects.

Algorithms↗
PubMed2001

A pilot randomized clinical trial on the relative effect of instrumental (MFMA) versus manual (HVLA) manipulation in the treatment of cervical spine dysfunction.

OBJECTIVE: To determine the relative effect of instrument-delivered thrust cervical manipulations in comparison with traditional manual-delivered thrust cervical manipulations in the treatment of cervical spine dysfunction. DESIGN: Prospective, randomized, comparative clinical trial. SETTING: Outpatient chiropractic clinic, Technikon Natal, South Africa. PATIENTS: Thirty patients diagnosed with neck pain and restricted cervical spine range of motion without complicating pathosis for at least 1 month were included in the study. INTERVENTIONS: The patients were randomized into 2 groups. Those in one group received mechanical force, manually assisted (MFMA) manipulation to the cervical spine, delivered by means of a hand-held instrument (Activator II Adjusting Instrument). Those in the other group received specific contact high-velocity, low-amplitude (HVLA) manipulation consisting of standard Diversified rotary/lateral break techniques to the cervical spine. Each group received only the specific therapeutic intervention, no other treatment modalities or interventions (including medication) being used, until asymptomatic status was achieved or a maximum of 8 treatments had been received. MAIN OUTCOME MEASURES: Both treatment groups were assessed through use of subjective (Numerical Pain Rating Scale 101, McGill Short-Form Pain Questionnaire, and Neck Disability Index) and objective (goniometer cervical range of motion) measurement parameters at specific intervals during the treatment period and at 1-month follow-up. The data were assessed through use of 2-tailed nonparametric paired and unpaired analysis, descriptive statistics, and power analysis of the data. RESULTS: The results indicate that both treatment methods had a positive effect on the subjective and objective clinical outcome measures, no significant difference being observed between the 2 groups (P < .025). The subjective data from all 3 questionnaires showed statistically significant changes from initial to final consultations as well as from initial consultation to 1-month follow-up (P < .025). The objective range of motion measures showed statistically significant changes in the MFMA group for left and right rotation and left and right lateral flexion from initial consultation to final consultations and for right rotation and right lateral flexion from initial consultation to 1-month follow-up. The HVLA group showed only the change in left rotation from initial to final consultations and from initial consultation to 1-month follow-up to be statistically significant. CONCLUSIONS: The results of this clinical trial indicate that both instrumental (MFMA) manipulation and manual (HVLA) manipulation have beneficial effects associated with reducing pain and disability and improving cervical range of motion in this patient population. A randomized, controlled clinical trial in a similar patient base with a larger sample size is necessary to verify the clinical relevance of these findings.

Adult↗
PubMedDate not supplied

[Oral contraceptives and breast cancer: analysis of the statistical power of the association].

The power of the association between oral contraceptives and breast cancer was analysed in all the papers published up to date. Seventy-seven publications (from 44 studies) were collected and graded as to quality using meta-analytical methods. Power achieved a figure of greater than or equal to 0.8 in a 10.8% of the associations studied. It showed a significant relationship with the existence of a significant relative risk of the oral contraceptives for breast cancer. The relationship with the sample size of a study was not linear. Power did not show any significant relationship to other variables related to the design of a study (apart from matching, being the power higher in unmatched studies), or to the biases detected, although studies considered as unbiased yielded a higher power. Logistic regression analysis included as predictors of a power greater than or equal to 0.80 the existence of a significant relative risk and the lack of biases in a research.

Analysis of Variance↗
PubMed1991

A new family of powerful multivariate statistical sequence analysis techniques.

A novel multivariate statistical approach is presented for extracting and exploiting intrinsic information present in our ever-growing sequence data banks. The information extraction from the sequences avoids the pitfalls of intersequence alignment by analyzing secondary invariant functions derived from the sequences in the data bank rather than the sequences themselves. Such typical invariant function is a 20 x 20 histogram of occurrences of amino acid pairs in a given sequence or fragment thereof. To illustrate the potential of the approach an analysis of 10,000 protein sequences from the National Biomedical Research Foundation Protein Identification Resource is presented, whose analysis already reveals great biological detail. For example, zeta-hemoglobin is found to lie close to amphibian and fish chi-hemoglobin which, in turn, is an important clue to the physiological function of this mammalian early embryonic hemoglobin. The multivariate statistical framework presented unifies such apparently unrelated issues as phylogenetic comparisons between a set of sequences and distance matrices between the constituents of the biological sequences. The Multivariate Statistical Sequence Analysis (MSSA) principles can be used for a wide spectrum of sequence analysis problems such as: assignment of family memberships to new sequences, validation of new incoming sequences to be entered into the database, prediction of structure from sequence, discrimination of coding from non-coding DNA regions, and automatic generation of an atlas of protein or DNA sequences. The MSSA techniques represent a self-contained approach to learning continuously and automatically from the growing stream of new sequences. The MSSA approach is particularly likely to play a significant role in major sequencing efforts such as the human genome project.

Amino Acid Sequence↗
PubMed2005

[Contribution to neglecting of power analysis in experimental medicine studies].

The work provides basic information about what is being understood under the term "statistical analysis of power of test" from the viewpoint of correct use of mathematical statistics in medicine. The detail rules of statistical decision-making are described. Furthermore, the work contains an illustration of power analysis of test application when using unpaired t-test.

Models, Statistical↗
PubMed2000

A power analysis of microsatellite-based statistics for inferring past population growth.

We present results concerning the power to detect past population growth using three microsatellite-based statistics available in the current literature: (1) that based on between-locus variability, (2) that based on the shape of allele size distribution, and (3) that based on the imbalance between variance and heterozygosity at a locus. The analysis is based on the single-step stepwise mutation model. The power of the statistics is evaluated for constant, as well as variable, mutation rates across loci. The latter case is important, since it is a standard procedure to pool data collected at a number of loci, and mutation rates at microsatellite loci are known to be different. Our analysis indicates that the statistic based on the imbalance between allele size variance and heterozygosity at a locus has the highest power for detection of population growth, particularly when mutation rates vary across loci.

Evolution, Molecular↗
PubMed2004

The power of statistical tests for moderators in meta-analysis.

Calculation of the statistical power of statistical tests is important in planning and interpreting the results of research studies, including meta-analyses. It is particularly important in moderator analyses in meta-analysis, which are often used as sensitivity analyses to rule out moderator effects but also may have low statistical power. This article describes how to compute statistical power of both fixed- and mixed-effects moderator tests in meta-analysis that are analogous to the analysis of variance and multiple regression analysis for effect sizes. It also shows how to compute power of tests for goodness of fit associated with these models. Examples from a published meta-analysis demonstrate that power of moderator tests and goodness-of-fit tests is not always high.

Humans↗
PubMed2006

Multivariable risk prediction can greatly enhance the statistical power of clinical trial subgroup analysis.

BACKGROUND: When subgroup analyses of a positive clinical trial are unrevealing, such findings are commonly used to argue that the treatment's benefits apply to the entire study population; however, such analyses are often limited by poor statistical power. Multivariable risk-stratified analysis has been proposed as an important advance in investigating heterogeneity in treatment benefits, yet no one has conducted a systematic statistical examination of circumstances influencing the relative merits of this approach vs. conventional subgroup analysis. METHODS: Using simulated clinical trials in which the probability of outcomes in individual patients was stochastically determined by the presence of risk factors and the effects of treatment, we examined the relative merits of a conventional vs. a "risk-stratified" subgroup analysis under a variety of circumstances in which there is a small amount of uniformly distributed treatment-related harm. The statistical power to detect treatment-effect heterogeneity was calculated for risk-stratified and conventional subgroup analysis while varying: 1) the number, prevalence and odds ratios of individual risk factors for risk in the absence of treatment, 2) the predictiveness of the multivariable risk model (including the accuracy of its weights), 3) the degree of treatment-related harm, and 5) the average untreated risk of the study population. RESULTS: Conventional subgroup analysis (in which single patient attributes are evaluated "one-at-a-time") had at best moderate statistical power (30% to 45%) to detect variation in a treatment's net relative risk reduction resulting from treatment-related harm, even under optimal circumstances (overall statistical power of the study was good and treatment-effect heterogeneity was evaluated across a major risk factor [OR = 3]). In some instances a multi-variable risk-stratified approach also had low to moderate statistical power (especially when the multivariable risk prediction tool had low discrimination). However, a multivariable risk-stratified approach can have excellent statistical power to detect heterogeneity in net treatment benefit under a wide variety of circumstances, instances under which conventional subgroup analysis has poor statistical power. CONCLUSION: These results suggest that under many likely scenarios, a multivariable risk-stratified approach will have substantially greater statistical power than conventional subgroup analysis for detecting heterogeneity in treatment benefits and safety related to previously unidentified treatment-related harm. Subgroup analyses must always be well-justified and interpreted with care, and conventional subgroup analyses can be useful under some circumstances; however, clinical trial reporting should include a multivariable risk-stratified analysis when an adequate externally-developed risk prediction tool is available.

Clinical Trials as Topic↗
PubMed1989

Sample size and statistical power in the hierarchical analysis of variance: applications in morphometry of the nervous system.

Analysis of variance is commonly used in morphometry in order to ascertain differences in parameters between several populations. Failure to detect significant differences between populations (type II error) may be due to suboptimal sampling and lead to erroneous conclusions; the concept of statistical power allows one to avoid such failures by means of an adequate sampling. Several examples are given in the morphometry of the nervous system, showing the use of the power of a hierarchical analysis of variance test for the choice of appropriate sample and subsample sizes. In the first case chosen, neuronal densities in the human visual cortex, we find the number of observations to be of little effect. For dendritic spine densities in the visual cortex of mice and humans, the effect is somewhat larger. A substantial effect is shown in our last example, dendritic segmental lengths in monkey lateral geniculate nucleus. It is in the nature of the hierarchical model that sample size is always more important than subsample size. The relative weight to be attributed to subsample size thus depends on the relative magnitude of the between observations variance compared to the between individuals variance.

Aging↗
PubMed1995

Pre mortem analysis of lung injury and lung function in oxygen toxic rabbits.

OBJECTIVES: To determine whether respiratory system mechanics measurements could detect lung injury in oxygen toxic rabbits before clinical deterioration. To determine whether respiratory system mechanics measurements, using a power analysis, have the statistical power to detect significant reductions in hyperoxic lung injury due to an intervention when compared with traditional post mortem measurements of lung injury, extravascular lung water, and bronchoalveolar lavage protein concentration. DESIGN: Prospective, controlled study. SETTING: Institutional animal laboratories. SUBJECTS: Adult New Zealand white rabbits. INTERVENTIONS: Spontaneously breathing adult New Zealand white rabbits were exposed continuously to either > 95% oxygen or room air. MEASUREMENTS AND MAIN RESULTS: We measured arterial pH, blood gas tensions, and respiratory system mechanics in rabbits twice, both before exposure to > 95% oxygen, and after the rabbits developed symptoms of mild lung dysfunction. After the second set of respiratory system mechanics measurements, we measured extravascular lung water and bronchoalveolar lavage protein concentration in the hyperoxia-exposed rabbits and compared the values with those values obtained in animals that breathed room air only. Our hyperoxia-exposed rabbits developed symptoms of mild respiratory impairment at 69 +/- 2 hrs. In these hyperoxia-exposed rabbits, measurements of static compliance, quasi-static compliance and resistance all changed significantly (p < .05) when compared with baseline measurements. Functional residual capacity and arterial blood gas values did not change significantly. Furthermore, assuming that an intervention reduced hyperoxic lung injury by a given amount, we performed a power analysis and found that the measurement of static compliance had at least equivalent power to detect a reduction in lung injury from an intervention when compared with measurement of extravascular lung water and bronchoalveolar lavage protein concentration. CONCLUSIONS: Measurements of respiratory system mechanics can detect lung injury in hyperoxic rabbits before the onset of severe clinical deterioration or death. Furthermore, measurement of static compliance of the respiratory system is likely to be a powerful tool to detect a reduction in lung injury produced by an intervention.

Airway Resistance↗
PubMed1990

Semen analysis and fertility assessment in rabbits: statistical power and design considerations for toxicology studies.

Semen analysis is commonly used in evaluating human response to reproductive toxicants. Serial semen samples can be collected from rabbits and fertility assessed by artificial insemination, hence this species is potentially well suited for male reproductive toxicity studies that might be extrapolated to humans. However, the size and cost of rabbits often restricts the number of animals used, reducing the sensitivity of such studies. Therefore, it was of interest to optimize study design for semen analysis and fertility assessment in rabbits. Semen samples were collected weekly from sexually mature New Zealand white rabbits and a range of parameters was analyzed (Semen--pH, volume, osmolality; Sperm--number and concentration, morphology, viability, percentage motility, motion characteristics; Seminal plasma--fructose, citric acid, carnitine and protein concentrations, acid phosphatase activity). Male fertility was assessed by inseminating female rabbits with the minimum number of motile sperm required for normal fertility, determined to be one million. The within- and between-buck variabilities were determined for all parameters and used to calculate the statistical power of different study designs. The variability of sperm number and concentration was decreased when measured in four ejaculates collected within a short period of time rather than in a single ejaculate; this was not true of other endpoints measured. In addition, use of preexposure observations further increased the statistical power for all of the parameters. These data can be used to determine the optimum design for studies of male reproductive toxicity using rabbits, with particular regard to cost and the number of animals used.

Acid Phosphatase↗