Demographics were compared by the Mann-Whitney U test and chi-squared test for continuous and categorical variables, respectively. To avoid eliminating data with missing values, Multiple Imputation in R was used. Missing values of the incomplete dataset were imputed m>1 times, thus creating m completed datasets. Second, each of the m completed datasets were independently analyzed. Finally, the results from each of the m analysis were pooled into a final result. Missing data like age, gender, and race were imputed by generating five similar but non-identical datasets. Groups were then matched by utilizing Coarsened Exact Matching in R , based on age, race, type of glaucoma, baseline IOP, and number of
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elsewhere [12,13]. First, this method is fast compared to multinomial regression. Second, it does not impose assumptions about the functional form and therefore, unlike regression, is unaffected if those assumptions are wrong. Matching is equivalent to a fully saturated multi- nomial model, including all pairwise and higher order interactions, but without assuming that treatment effects are constant. Using a matching algorithm results in an algorithm that is insensitive to analysts' choices about whether to include interactions and higher order terms . Third, we do not assume parameter constancy (that all of the predictor variables mean the same thing for all observations). This assumption may not hold if the varia- tion in the parameters is related to the relatively small number of available covariates. If this is the case, the results would very likely be biased. Fourth, logistic regression can be biased if its crucial "independence of irrelevant alternatives" assumption is violated; coarsened exact matching is not biased whether or not this assump- tion holds. An implication of this is that the outcome cat- egories need not be broad and distinct when coarsened exact matching is used. Finally, an important related advantage of matching is that it does not require the ana- lyst to select the underlying causes of death to which ill- defined deaths are reassigned. In fact, it identifies the causes of death with which specific ill-defined causes of death are associated. For example, it is implausible that heart failure is in the causal chain for cancers, yet certify- ing physicians frequently list heart failure and cancers together on the death certificate. This method identifies that association and redistributes heart failure deaths accordingly. A multinomial regression using the match
It is more likely to neglect other potential confound- ing influences of different comparison groups that may result in health inequity  by roughly com- paring the income-related inequity of HRQoL be- tween different health insurance schemes. Therefore, we applied the coarsened exact matching (CEM) method, firstly proposed by Lacus, et al. [23, 24] to keep better balance of distributions of the covariates between the comparison groups and thereby redu- cing the biases. In general, the basic algorithm of CEM mainly includes three procedures. Firstly, each variable is coarsened by recoding to group and ap- point the indistinguishable values with the same value. In the second step, the algorithm of exact matching is employed. And then removing the coars- ened data, the final matched data should be reserved [23, 24]. A weighting variable generated by CEM method is used to equalize the number of observa- tions within comparison groups [23, 24]. For balance checking, multivariate imbalance measure L 1 was
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analysis alone can be misleading [5-7]. To overcome these issues in comparing the sexes, we improved the balance within the groups in a first step by coarsened exact match- ing (CEM) , thereby neglecting outcome and safety variables. To account for the remaining bias in covariates and to estimate outcome, we then performed adjusted regression analysis. This two-step approach is less prone to model misspecification and even more robust than are results based on the full unmatched data set [7,9,10].
Realization of the clinical application of these enor- mous amounts of data will depend on the blending of evidence-based medicine from traditional clinical study sources together with ‘big data’ methods . Addition of classification, data mining, and predictive analytic techniques have already enabled insights [14, 18], and additional efforts are required, such as those that can better link observational data with randomized data. Cameron et al. (2015) reviewed the advantages, disad- vantages, and methodological challenges of linking the two types of studies in network meta-analyses and em- phasized the importance of such efforts in generating evidence from across a medication’s lifecycle given the growth in analyses of post-approval data that needs to be combined with pre-approval data . While tradi- tional statistical techniques such as meta-analyses and network meta-analyses have supported linkage of differ- ent studies, they still generate population-level results, which require the clinician to further extrapolate them to individual patient treatment decisions. Improved methodological techniques for connecting data at the patient level are being developed (e.g., Iacus et al. (2012) on Coarsened Exact Matching (CEM) ) and provide better ways of integrating data from observational stud- ies and RCTs. This goal of integrating RCT and observa- tional study data guided our effort, and we started with the specific case of pain response in pDPN to treatment with the α2δ ligand, pregabalin, to demonstrate a proof of concept as to how such data integration could be im- plemented to improve outcomes. Understanding which patients are going to have a better-than-average response to treatment may shed light on the possible improvements in care that could increase the proportion of good re- sponders. Efforts have evolved during the past two decades to predict individual patient responses via predictive ana- lytics and simulation building on the pioneering work of David Eddy (2012) .
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Background: Heart failure is sometimes incorrectly listed as the underlying cause of death (UCD) on death certificates, thus compromising the accuracy and comparability of mortality statistics. Statistical redistribution of the UCD has been used to examine the effect of misclassification of the UCD attributed to heart failure, but sex- and race-specific redistribution of deaths on coronary heart disease (CHD) mortality in the United States has not been examined. Methods: We used coarsened exact matching to infer the UCD of vital records with heart failure as the UCD from 1999 to 2010 for decedents 55 years old and older from states encompassing regions under surveillance by the Atherosclerosis Risk in Communities (ARIC) Study (Maryland, Minnesota, Mississippi, and North Carolina). Records with heart failure as the UCD were matched on decedent characteristics (five-year age groups, sex, race, education, year of death, and state) to records with heart failure listed among the multiple causes of death. Each heart failure death was then redistributed to plausible UCDs proportional to the frequency among matched records.
2.2 Coarsened exact matching CEM is a member of the MIB class that is used here, in part, because it is easily applied to large databases with SQL code. More significantly, CEM-based estimates have many desirable statistical properties (Iacus et al. , 2011a,b). It has been shown that CEM dominates commonly used matching methods (EPBR and others) as measured by its ability to reduce imbalance, model dependence, estimation er- ror, bias, variance, mean square error, and other criteria for a range of data sets (Iacus et al. , 2011a,b).
The observation underpinning this paper is that edit-distance represents an elegant alternative to the exhaustive compilation of dictionaries. Specifically, it provides a means by which structural errors can be modeled in an implicit rather than an explicit manner. Our goal is to follow Wilson and Hancock ,  by modeling the probability distribution for edit-distance. We commence with a simple memoryless distribution rule over the basic edit operations. This leads to an exponential distribution. Although it can be shown that the dictionary-based graph- matching technique requires a polynomial number of dictionary comparisons, relatively little attention has been paid to the time and space complexity of dictionary compilation and lookup. In the original work on discrete relaxation, Waltz  had a large but fixed set of dictionaries for line labeling. Because it models structural error by padding out and permuting the nodes of graphs of different size, Wilson and Hancock's dictionary can grow exponentially. Although this growth can be curbed using relatively unobjectionable heuristics, the aim in this paper is to take a more principled approach. By adopting the edit-distance as our measure of similarity, we remove the need for dictionary padding and reduce the worst-case complexity to be polynomial. In an experimental study, we show that even a relatively naõÈve application of the edit-distance approach performs no worse than the original, and can do significantly better under certain circumstances.
One approach calculates the longest repeated subsequences (LRSs) to find identical subsequences of two or more links. For example, comparing Sequences 1 and 2 (see Figure 1a) there are LRSs of length three (ABC) and two (DE). In practice it is rare to find long LRSs in hypertext navigation, and in one study the overwhelming majority had a length <= 3 . However, many of the sequences were similar (most links were the same, but at least one in each sequence was unique), which led to the suggestion that inexact string matching would be more appropriate.
Academic users are guided in the content of bibliographic databases through matching their search keywords that match the keywords used by any retrieval system or database for indexing. The mismatch of searched keywords and in- dexed keywords in databases may result in retrieval failure in accessing informa- tion. This can hinder scientific production particularly within databases provid- ing full-text scientific articles. The effectiveness and value of these databases are subject to provision of services and appropriate approaches for enabling users in searching and quick and easy access to journals . The search ability of a full-text database requires indexing, the implementation of this is one of the main processes in development of such databases capable of guiding the re- searcher on the content of any scientific document .
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The semantic matching process has run as it was hoped previously. It is proven by the result of the system testing which has been able to display the relevant web service although the keyword of the query searching uses different syntax mentioned in their own web service description. However, it has semantic relationship based on the defined ontology. The capability is the one that is not owned by UDDI in which the searching process will find out the result if the searching query has the same syntax as the web service description . Beside that, the degree of match in UDDI’s discovery service only uses two levels, namely EXACT and FAIL. Meanwhile the discovery service in the research uses four degrees of match, namely EXACT, PLUG_IN, SUBSUME and FAIL. 7. CONCLUSION
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variation in background matching between the morphs. Instead, the incidence of plain-backed morph which has the greatest contrast from their background is highest in low latitudes and lowest in high latitudes, mirroring the pattern of predation intensity. This implies that either background matching among the two colour morphs could vary between populations due to variability in habitat structure or predator communities resulting in different levels of crypsis. Or, other selective forces (i.e., frequency-dependent selection), behavioural differences (i.e., differential dispersal abilities: Forsman et al. 2008; Grant & Liebgold 2017), variation in physiology (i.e., thermal tolerances: Bozinovic et al. 2011), or non-adaptive processes (i.e., gene flow) not considered here may be occurring across populations and act in producing the observed latitudinal variation in morph frequency in this species. These additional factors should, therefore, be evaluated across populations to help elucidate the underpinnings of colour polymorphism within L. whitii.
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In order to design the policy rules, we use an algorithmic linear feedback control technique known as (exact) model matching control. It is a completely parameterized technique allowing us to develop appropriate symbolic algorithms in order to design the requested policy rules. One of the main advantages of this approach is that we obtain as a solution a class of feedback policy rules; this grants the policymaker the ability to choose the most appropriate policy rule from the set of potential policies available, depending on the particular case at hand. Moreover, the policy rules take into account the state of the economy, since they incorporate the relevant information available up to the decision period, and they are responsive (i.e., the coefficients of the algebraic expres- sions are not fixed), thus representing a more discretionary approach to the design of fiscal policy.
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and can be unstable in practice if some probabilities of observing the full data are close to zero. Robins et al. (1994) also identified a class of “augmented” inverse probability weighted estima- tors that, in the present context, involve (parametric) modeling of both the coarsening probabilities and the conditional expectations of certain functions of the full data given the coarsened data for each level of coarsening; see Section 2.3. The efficient member of this class, that with smallest asymptotic variance, is obtained when both sets of models are correctly specified. Scharfstein et al. (1999) noted that estimators in this class are consistent even if one of the sets of models (but not both) is misspecified. Estimators with this property are referred to as “doubly robust” and have been advocated owing to the protection this feature affords (Bang and Robins, 2005). Bang and Robins (2005) described such a doubly robust estimator in the case of a longitudinal study with dropout and provided simulation evidence demonstrating the doubly robust property; see also Seaman and Copas (2009).
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The simulation of floating inductance with less number of commercially available active devices with single grounded capacitor is one of important aspect of design in filter application. The tunable property of transconductance gain of OTA, the simulation of floating inductance with 2-OTA gives exactly matching frequencies with less error compared with 5-OTA, 4-OTA and 3-OTA low pass responses. The negative inductance simulation cut off frequencies matches with -6dB frequencies, which shows Bessel’s filter characters. It is concluded that 2-OTA floating inductance simulation of positive and negative inductance is considered to be more suitable in LC ladder filter structures.
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The dispersion pro ﬁ le of a non-linear optical material determines its phasematching characteristics and thus mainly dictates the spectral characteristics of the PDC emission. Apart from the exact phasematching wavelength given by the effective index matching of the interacting pump, signal and idler modes, the knowledge of the group refractive index and its dispersion are crucial for predicting the properties of the signal and idler. We have utilized the well-known Fabry – Perot method to access the group indices at the pump and PDC wavelengths in order to estimate the phasematching bandwidth. Additionally, we have recorded spectral marginal distributions for the signal and idler to infer their group index difference and to acquire an approximation for their group index dispersion. Our results demonstrate a straightforward method to access the spectral PDC process parameters by making only few frequency- resolved measuremements and provide the means for ver- ifying and controlling the performance of highly sophisti- cated, multi-layered PDC emitters.
populations naturally suffer from bias as is evident in our own pre-match data. Our AIT patients had a higher IOP than TBS before matching suggesting that AIT was a surgeon preference in individuals with higher pressure. AIT lowered the IOP by approximately 13% to 13.9 mm Hg and decreased the number of medications by less than one while maintaining a low rate of serious complications. As seen in previous reports, 1,35 IOP and medications needed to achieve this IOP remained mostly stable. In this study, we found
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A key prediction of landmark-matching is that animals will search at the location that best preserves either the remem- bered apparent size or the remembered retinal position of land- marks. When birds searched at the correct absolute distance, this was therefore seen as evidence against view-matching. Even before Cartwright and Collett published their model, however, honeybees had been seen to search at the absolute distance from enlarged landmarks (Cartwright & Collett, 1979), a finding since replicated in wasps (Zeil, 1993b) and other bee species (Brunnert, Kelber, & Zeil, 1994). Rather than using apparent size, these flying insects appear to esti- mate distance using motion parallax: the relationship between the distance to an object and the speed at which it moves across the visual field, its optic flow (Gibson, 1979; Koenderink, 1986). In addition to sensing the distance of vi- sual objects (Lehrer & Collett, 1994; Lehrer et al., 1988; Srinivasan, Lehrer, Zhang, & Horridge, 1989), bees can also navigate using only patterns of optic flow, searching accurate- ly relative to landmarks that can be seen only when the bees move (Dittmar et al., 2010). This depth-matching strategy seems similar to landmark-matching but is based on matching remembered patterns of optic flow rather than learned retinal angles. The B optic-flow snapshot ^ used by depth-matching
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The paper is structured as follows. The next section describes briefly why the old assault guideline was considered inadequate and the changes which were made in the new guideline. This background will help us understand and explain some of our empirical findings. Section 3 describes the methodological challenges of measuring consistency in sentencing and presents two solutions that we will consider in our analysis. Section 4 introduces the Crown Court Sentencing Survey (CCSS) a new dataset capturing most relevant characteristics of the offence and the offender sentenced in the Crown Courts in 2011. In Section 5 we describe the implementation of the two methods that we use to assess changes in consistency across time, the study of the dispersion of residuals and exact matching. Section 6 concludes with a summary of our results, a discussion of the caveats, and future research paths.
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(particularly in the analysis of overall asthma control for which adjustments in some other methods made quite large differences), suggesting that the matching was effective in reducing confounding. All models were adjusted for evidence of gastroesophageal reflux disease (GERD). This was not a matching variable and significant differences (41% vs. 34% in ciclesonide vs. fine-particle cohorts) remained at baseline after matching; standardized differences were in excess of 10%. Calculation of the propensity score showed this to be a strong predictor of treatment allocation, which maybe could have been improved by using the propensity score to influ- ence choice of exact matching criteria. It would have been interesting to repeat the exact matching process, matching also on evidence of GERD, although the gain in balance across treatment arms would need to be weighed against a further loss in sample size and therefore power.
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