69 resultados para Factorial validity
Resumo:
BACKGROUND Current reporting guidelines do not call for standardised declaration of follow-up completeness, although study validity depends on the representativeness of measured outcomes. The Follow-Up Index (FUI) describes follow-up completeness at a given study end date as ratio between the investigated and the potential follow-up period. The association between FUI and the accuracy of survival-estimates was investigated. METHODS FUI and Kaplan-Meier estimates were calculated twice for 1207 consecutive patients undergoing aortic repair during an 11-year period: in a scenario A the population's clinical routine follow-up data (available from a prospective registry) was analysed conventionally. For the control scenario B, an independent survey was completed at the predefined study end. To determine the relation between FUI and the accuracy of study findings, discrepancies between scenarios regarding FUI, follow-up duration and cumulative survival-estimates were evaluated using multivariate analyses. RESULTS Scenario A noted 89 deaths (7.4%) during a mean considered follow-up of 30±28months. Scenario B, although analysing the same study period, detected 304 deaths (25.2%, P<0.001) as it scrutinized the complete follow-up period (49±32months). FUI (0.57±0.35 versus 1.00±0, P<0.001) and cumulative survival estimates (78.7% versus 50.7%, P<0.001) differed significantly between scenarios, suggesting that incomplete follow-up information led to underestimation of mortality. Degree of follow-up completeness (i.e. FUI-quartiles and FUI-intervals) correlated directly with accuracy of study findings: underestimation of long-term mortality increased almost linearly by 30% with every 0.1 drop in FUI (adjusted HR 1.30; 95%-CI 1.24;1.36, P<0.001). CONCLUSION Follow-up completeness is a pre-requisite for reliable outcome assessment and should be declared systematically. FUI represents a simple measure suited as reporting standard. Evidence lacking such information must be challenged as potentially flawed by selection bias.
Resumo:
OBJECTIVES To assess the clinical profile and long-term mortality in SYNTAX score II based strata of patients who received percutaneous coronary interventions (PCI) in contemporary randomized trials. BACKGROUND The SYNTAX score II was developed in the randomized, all-comers' SYNTAX trial population and is composed by 2 anatomical and 6 clinical variables. The interaction of these variables with the treatment provides individual long-term mortality predictions if a patient undergoes coronary artery bypass grafting (CABG) or PCI. METHODS Patient-level (n=5433) data from 7 contemporary coronary drug-eluting stent (DES) trials were pooled. The mortality for CABG or PCI was estimated for every patient. The difference in mortality estimates for these two revascularization strategies was used to divide the patients into three groups of theoretical treatment recommendations: PCI, CABG or PCI/CABG (the latter means equipoise between CABG and PCI for long term mortality). RESULTS The three groups had marked differences in their baseline characteristics. According to the predicted risk differences, 5115 patients could be treated either by PCI or CABG, 271 should be treated only by PCI and, rarely, CABG (n=47) was recommended. At 3-year follow-up, according to the SYNTAX score II recommendations, patients recommended for CABG had higher mortality compared to the PCI and PCI/CABG groups (17.4%; 6.1% and 5.3%, respectively; P<0.01). CONCLUSIONS The SYNTAX score II demonstrated capability to help in stratifying PCI procedures.
Resumo:
The Culture Fair Test (CFT) is a psychometric test of fluid intelligence consisting of four subtests; Series, Classification, Matrices, and Topographies. The four subtests are only moderately intercorrelated, doubting the notion that they assess the same construct (i.e., fluid intelligence). As an explanation of these low correlations, we investigated the position effect. This effect is assumed to reflect implicit learning during testing. By applying fixed-links modeling to analyze the CFT data of 206 participants, we identified position effects as latent variables in the subtests; Classification, Matrices, and Topographies. These position effects were disentangled from a second set of latent variables representing fluid intelligence inherent in the four subtests. After this separation of position effect and basic fluid intelligence, the latent variables representing basic fluid intelligence in the subtests Series, Matrices, and Topographies could be combined to one common latent variable which was highly correlated with fluid intelligence derived from the subtest Classification (r=.72). Correlations between the three latent variables representing the position effects in the Classification, Matrices, and Topographies subtests ranged from r=.38 to r=.59. The results indicate that all four CFT subtests measure the same construct (i.e., fluid intelligence) but that the position effect confounds the factorial structure
Resumo:
The aim of the present study was to develop a pictorial presence scale using selfassessment- manikins (SAM). The instrument assesses presence sub-dimensions (selflocation and possible actions) as well as presence determinants (attention allocation, spatial situation model, higher cognitive involvement, and suspension of disbelief). To qualitatively validate the scale, think-aloud protocols and interviews (n = 12) were conducted. The results reveal that the SAM items are quickly filled out as well as easily, intuitively, and unambiguously understood. Furthermore, the instrument’s validity and sensitivity was quantitatively examined in a two-factorial design (n = 317). Factors were medium (written story, audio book, video, and computer game) and distraction (non-distraction vs. distraction). Factor analyses reveal that the SAM presence dimensions and determinants closely correspond to those of the MEC Spatial Presence Questionnaire, which was used as a comparison measure. The findings of the qualitative and quantitative validation procedures show that the Pictorial Presence SAM successfully assesses spatial presence. In contrast to the verbal questionnaire data (MEC), the significant distraction effect suggests that the new scale is even more sensitive. This points out that the scale can be a useful alternative to existing verbal presence selfreport measures.
Resumo:
Bayesian clustering methods are typically used to identify barriers to gene flow, but they are prone to deduce artificial subdivisions in a study population characterized by an isolation-by-distance pattern (IbD). Here we analysed the landscape genetic structure of a population of wild boars (Sus scrofa) from south-western Germany. Two clustering methods inferred the presence of the same genetic discontinuity. However, the population in question was characterized by a strong IbD pattern. While landscape-resistance modelling failed to identify landscape features that influenced wild boar movement, partial Mantel tests and multiple regression of distance matrices (MRDMs) suggested that the empirically inferred clusters were separated by a genuine barrier. When simulating random lines bisecting the study area, 60% of the unique barriers represented, according to partial Mantel tests and MRDMs, significant obstacles to gene flow. By contrast, the random-lines simulation showed that the boundaries of the inferred empirical clusters corresponded to the most important genetic discontinuity in the study area. Given the degree of habitat fragmentation separating the two empirical partitions, it is likely that the clustering programs correctly identified a barrier to gene flow. The differing results between the work published here and other studies suggest that it will be very difficult to draw general conclusions about habitat permeability in wild boar from individual studies.