Showing papers on "Matching (statistics) published in 2001"

Active appearance models

Abstract: We describe a new method of matching statistical models of appearance to images. A set of model parameters control modes of shape and gray-level variation learned from a training set. We construct an efficient iterative matching algorithm by learning the relationship between perturbations in the model parameters and the induced image errors.

Looking into the Black Box: A Survey of the Matching Function

Abstract: This paper surveys the microfoundations, empirical evidence, and estimation issues underlying the aggregate matching function. There is no consensus yet on microfoundations but one is emerging on estimation. An aggregate, constant returns, Cobb-Douglas matching function with hires as a function of vacancies and unemployment has been successfully estimated for several countries. Recent work has utilized disaggregated data to go beyond aggregate estimates, with many refinements and suggestions for future research. The paper discusses spatial aggregation issues, and implications of on-the-job search and of the timing of stocks and flows for estimated matching functions.

Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation

Abstract: Propensity score methodology can be used to help design observational studies in a way analogous to the way randomized experiments are designed: without seeing any answers involving outcome variables. The typical models used to analyze observational data (e.g., least squares regressions, difference of difference methods) involve outcomes, and so cannot be used for design in this sense. Because the propensity score is a function only of covariates, not outcomes, repeated analyses attempting to balance covariate distributions across treatment groups do not bias estimates of the treatment effect on outcome variables. This theme will the primary focus of this article: how to use the techniques of matching, subclassification and/or weighting to help design observational studies. The article also proposes a new diagnostic table to aid in this endeavor, which is especially useful when there are many covariates under consideration. The conclusion of the initial design phase may be that the treatment and control groups are too far apart to produce reliable effect estimates without heroic modeling assumptions. In such cases, it may be wisest to abandon the intended observational study, and search for a more acceptable data set where such heroic modeling assumptions are not necessary. The ideas and techniques will be illustrated using the initial design of an observational study for use in the tobacco litigation based on the NMES data set.

Pricing and Matching with Frictions

Abstract: Suppose that n buyers each want one unit and m sellers each have one or more units of a good. Sellers post prices, and then buyers choose sellers. In symmetric equilibrium, similar sellers all post one price, and buyers randomize. Hence, more or fewer buyers may arrive than a seller can accommodate. We call this frictions. We solve for prices and the endogenous matching function for finite n and m and consider the limit as n and m grow. The matching function displays decreasing returns but converges to constant returns. We argue that the standard matching function in the literature is misspecified and discuss implications for the Beveridge curve.

Endogenous Matching and the Empirical Determinants of Contract Form

Abstract: Empirical work on contracts typically regresses contract choice on observed principal and agent characteristics. If (i) some of these characteristics are unobserved or partially observed, and (ii) there are incentives whereby particular types of agents end up contracting with particular types of principals, estimated coefficients on the observed characteristics may be misleading. We address this endogenous matching problem using a data set on agricultural contracts between landlords and tenants in early Renaissance Tuscany. Controlling for endogenous matching has an impact on parameters of interest and tenants' risk aversion appears to have influenced contract choice.

Matching/mismatching revisited: an empirical study of learning and teaching styles

Abstract: This paper presents results of a research project that explored the relationship between matching and mismatching instructional presentation style (breadth-first and depth-first) with students' cognitive style (field-dependence/-independence) in a computer-based learning environment. 73 postgraduate students were asked to create Web pages using HTML, using instructional materials that were either matched or mismatched with their cognitive styles. Significant differences in performance on a multiple choice test of conceptual knowledge were found for students learning in matched and mismatched conditions. Performance in matched conditions was significantly superior to that in mismatched conditions. However, significant effects were found for gender, matching mainly affecting male students. Performance on a practical test of Web page creation was not linked to matching or mismatching, but was linked to an interaction between gender and instructional presentation style. The findings provide support for the notion that matching and mismatching can have significant effects on learning outcomes. The paper concludes with suggestions for further research.

Reconciling Conflicting Evidence on the Performance of Propensity-Score Matching Methods

Abstract: There is a long-standing debate in the literature over whether social programs can be reliably evaluated without a randomized experiment. This paper summarizes results from a larger paper (Smith and Todd, 2001) that uses experimental data combined with nonexperimental data to evaluate the performance of alternative nonexperimental estimators. The impact estimates based on experimental data provide a benchmark against which to judge the performance of nonexperimental estimators. Our experimental data come from the National Supported Work (NSW) Demonstration and the nonexperimental data from the Current Population Survey (CPS) and the Panel Study of Income Dynamics (PSID). These same data were used in influential papers by Robert LaLonde (1986), James Heckman and Joseph Hotz (1989), and Rajeev Dehejia and Sadek Wahba (1998, 1999). We focus on a class of estimators called propensity-score matching estimators, which were introduced in the statistics literature by Paul Rosenbaum and Donald Rubin (1983). Traditional propensity-score matching methods pair each program participant with a single nonparticipant, where pairs are chosen based on the degree of similarity in the estimated probabilities of participating in the program (the propensity scores). More recently developed nonparametric matching estimators described in Heckman et al. (1997, 1998a, b) use weighted averages over multiple observations to construct matches. We apply both kinds of estimators in this paper. Heckman et al. (1997, 1998a, b) evaluate the performance of matching estimators using experimental data from the U.S. National Job Training Partnership Act (JTPA) Study combined with comparison group samples drawn from three sources. They show that data quality is a crucial ingredient to any reliable estimation strategy. Specifically, the estimators they examine are only found to perform well in replicating the results of the experiment when they are applied to comparison group data satisfying the following criteria: (i) the same data sources (i.e., the same surveys or the same type of administrative data or both) are used for participants and nonparticipants, so that earnings and other characteristics are measured in an analogous way, (ii) participants and nonparticipants reside in the same local labor markets, and (iii) the data contain a rich set of variables relevant to modeling the program-participation decision. If the comparison group data fails to satisfy these criteria, the performance of the estimators diminishes greatly. More recently, Dehejia and Wahba (1998, 1999) have used the NSW data (also used by LaLonde) to evaluate the performance of propensity-score matching methods, including pairwise matching and caliper matching. They find that these simple matching estimators succeed in closely replicating the experimental NSW results, even though the comparison group data do not satisfy any of the criteria found to be important in Heckman et al. (1997, 1998a). From this evidence, they conclude that matching approaches are generally more reliable than traditional econometric estimators. In this paper, we reanalyze the NSW data in an attempt to reconcile the conflicting findings * Smith: Department of Economics, University of Western Ontario, Social Science Centre, London, ON, N6A 5C2, Canada, and NBER; Todd: Department of Economics, University of Pennsylvania, 3718 Locust Walk, Philadelphia, PA 19104, and NBER. Versions of the paper that is the source for this paper have been presented at a 2000 meeting of the Institute for Research on Poverty in Madison, Wisconsin, at the Western Research Network on Employment and Training summer workshop (August 2000), at the Canadian International Labour Network meetings (September 2000), and at the University of North Carolina. We thank James Heckman for comments on this paper, and we thank Robert LaLonde for comments and for providing us with the data from his 1986 study. We thank Rajeev Dehejia for providing us with information helpful in reconstructing the samples used in the Dehejia and Wahba (1998, 1999) studies. Jingjing Hsee and Miana Plesca provided excellent research assistance.

Fingerprint matching using minutiae and texture features

Abstract: The advent of solid-state fingerprint sensors presents a fresh challenge to traditional fingerprint matching algorithms. These sensors provide a small contact area (/spl ap/0.6"/spl times/0.6") for the fingertip and, therefore, sense only a limited portion of the fingerprint. Thus multiple impressions of the same fingerprint may have only a small region of overlap. Minutiae-based matching algorithms, which consider ridge activity only in the vicinity of minutiae points, are not likely to perform well on these images due to the insufficient number of corresponding points in the input and template images. We present a hybrid matching algorithm that uses both minutiae (point) information and texture (region) information for matching the fingerprints. Results obtained on the MSU-VERIDICOM database shows that a combination of the texture-based and minutiae-based matching scores leads to a substantial improvement in the overall matching performance.

Method and system for facilitating service transactions

Abstract: A computer-implemented method and system for facilitating service transactions, both on-line and off-line, for transacting services driven by purchasers or by service providers. In particular, the invention makes services freely tradable as goods via standardizing material terms describing such service transactions. The method includes steps defining a set of service classification and material terms, registering a plurality of participants of the service marketplace, searching and compiling at least one offer and one request for offers provided by the participants for selling or buying services while the offer and the request for offer is described in the set of service classification and material terms, evaluating and matching the offer and the request for offer based upon the degree of identicalness of the set of service classification and material terms recited in the offer and the request for offer, and communicating to matched participants of the result generated by the evaluating and matching step.

Bounding a matching estimator: the case of a Norwegian training program

Abstract: In this paper we evaluate a Norwegian vocational training rehabilitation program by comparing employment outcomes of trainees and nonparticipants using nonexperimental data. A matching estimator is used to calculate the training effect for different subgroups of the sample. We demonstrate how bounding the matching estimator can be used to evaluate the intrinsic uncertainty of estimated training effects due to selection on unobserved individual characteristics. After adjustment for observed selection into training programs we find that the overall training effect is around six percentage points. This is mainly due to a high and significant effect for individuals with a low probability of program participation. After calculating upper and lower bounds on the test statistics used to test the hypothesis of no training effect we find that the overall effect is sensitive to unobserved selection. However, the result that the training effect is positive for individuals who are less likely to participate in a training program is not sensitive to selection bias. These individuals also have the lowest employment probabilities, which indicates potential harmful cream skimming in the Norwegian vocational rehabilitation sector.Copyright 2001 by Blackwell Publishing Ltd

The Impact of Activity‐Based Costing Techniques on Firm Performance

Abstract: Given the debate in both the professional and scholarly literature on the effectiveness of management accounting systems in the contemporary business environment, there is a need to understand more about the impact of activity‐based costing (ABC). In this paper, we show that the choice of a management accounting system, such as ABC, may have a significant impact on firm value. Specifically, for a sample of U.K. firms, we show that firms adopting activity‐based costing techniques outperform matched non‐ABC firms by approximately 27 percent over the three years beginning on January 1 of the year in which the ABC techniques are first implemented. This result is robust to different matching criteria and for both accounting and market‐based measures of performance. Further analysis suggests that ABC adds to firm value through better cost controls and asset utilization, coupled with greater use of financial leverage.

Computer-aided photograph matching in studies using individual identification: an example from serengeti cheetahs

Abstract: Photographic identification of naturally marked animals is a powerful and nonintrusive technique for obtaining information on behavior, population size, and life-history parameters in wild populations. Yet handling large quantities of photographs is time consuming and prone to error. Computer-aided matching can limit the number of photographs that must be examined visually to confirm that 2 sightings are the same individual. To identify individuals, I used a 3-dimensional (3-D) computer-matching system to aid in matching nearly 10,000 photographs of Serengeti cheetahs, Acinonyx jubatus, taken over 25 years. Accuracy in matching 2 photographs increased to 100% as the computer-generated similarity coefficient increased to 0.600 on a scale from 0 to 1. Probability of missing a match decreased to 6.4% when I used a threshold of similarity of 0.450. Poor quality of photographs decreased accuracy and resulted in up to 33% of matches being missed. Comparisons of photographs at skewed camera angles generally reduced similarity coefficients. Similarity coefficients were no higher for related or unrelated animals, suggesting that the technique is not appropriate for distinguishing subtle similarities. Because 3-D computer-aided matching does not require familiarity with distinctive features of the particular study animal, it is robust to matcher inexperience. This technique can be modified for other species that have complex and variable pelage patterns.

Matching With Doses in an Observational Study of a Media Campaign Against Drug Abuse

Abstract: Multivariate matching with doses of treatment differs from the treatment-control matching in three ways First, pairs must not only balance covariates, but also must differ markedly in dose Second, any two subjects may be paired, so that the matching is nonbipartite, and different algorithms are required Finally, a propensity score with doses must be used in place of the conventional propensity score We illustrate multivariate matching with doses using pilot data from a media campaign against drug abuse The media campaign is intended to change attitudes and intentions related to illegal drugs, and the evaluation compares stated intentions among ostensibly comparable teens who reported markedly different exposures to the media campaign

Fast block matching algorithm based on the winner-update strategy

Abstract: Block matching is a widely used method for stereo vision, visual tracking, and video compression. Many fast algorithms for block matching have been proposed in the past, but most of them do not guarantee that the match found is the globally optimal match in a search range. This paper presents a new fast algorithm based on the winner-update strategy which utilizes an ascending lower bound list of the matching error to determine the temporary winner. Two lower bound lists derived by using partial distance and by using Minkowski's inequality are described. The basic idea of the winner-update strategy is to avoid, at each search position, the costly computation of the matching error when there exists a lower bound larger than the global minimum matching error. The proposed algorithm can significantly speed up the computation of the block matching because (1) computational cost of the lower bound we use is less than that of the matching error itself; (2) an element in the ascending lower bound list will be calculated only when its preceding element has already been smaller than the minimum matching error computed so far; (3) for many search positions, only the first several lower bounds in the list need to be calculated. Our experiments have shown that, when applying to motion vector estimation for several widely-used test videos, 92% to 98% of operations can be saved while still guaranteeing the global optimality. Moreover, the proposed algorithm can be easily modified either to meet the limited time requirement or to provide an ordered list of best candidate matches.

Balanced Risk Set Matching

Abstract: A new form of matching–optimal balanced risk set matching–is applied in an observational study of a treatment, cystoscopy and hydrodistention, given in response to the symptoms of the chronic, nonlethal disease interstitial cystitis. When a patient receives the treatment at time t, that patient is matched to another patient with a similar history of symptoms up to time t who has not received the treatment up to time t; this is risk set matching. By using a penalty function in integer programming in a new way, we force the marginal distributions of symptoms to be balanced in the matched treated and control groups. Among all balanced matchings, we pick the one that is optimal in the sense of minimizing the multivariate pretreatment covariate distance within matched pairs. Under a simple model for the treatment assignment mechanism, we study the sensitivity of the findings to hidden biases. In particular, we show that a simple, conventional sensitivity analysis is appropriate with risk set matching when the ...

Fast Content-Based Packet Handling for Intrusion Detection

Abstract: It is becoming increasingly common for network devices to handle packets based on the contents of packet payloads. Example applications include intrusion detection, firewalls, web proxies, and layer seven switches. This paper analyzes the problem of intrusion detection and its reliance on fast string matching in packets. We show that the problem can be restructured to allow the use of more efficient string matching algorithms that operate on sets of patterns in parallel. We then introduce and analyze a new string matching algorithm that has average-case performance that is better than the best theoretical algorithm (Aho-Corasick) and much better than the currently deployed algorithm (multiple iterations of Boyer-Moore). Finally, we implement these algorithms in the popular intrusion detection platform Snort and analyze their relative performance on actual packet traces. Our results provide lessons on the structuring of content-based handlers, string matching algorithms in general, and the importance of performance to security.

Scalable high-speed prefix matching

Abstract: Finding the longest matching prefix from a database of keywords is an old problem with a number of applications, ranging from dictionary searches to advanced memory management to computational geometry. But perhaps today's most frequent best matching prefix lookups occur in the Internet, when forwarding packets from router to router. Internet traffic volume and link speeds are rapidly increasing; at the same time, a growing user population is increasing the size of routing tables against which packets must be matched. Both factors make router prefix matching extremely performance critical.In this paper, we introduce a taxonomy for prefix matching technologies, which we use as a basis for describing, categorizing, and comparing existing approaches. We then present in detail a fast scheme using binary search over hash tables, which is especially suited for matching long addresses, such as the 128 bit addresses proposed for use in the next generation Internet Protocol, IPv6. We also present optimizations that exploit the structure of existing databases to further improve access time and reduce storage space.

On Matching Schemas Automatically

Abstract: Schema matching is a basic problem in many database application domains, such as data integration,E-business, data warehousing, and semantic query processing. In current implementations, schemamatching is typically performed manually, which has significant limitations. On the other hand, inprevious research many techniques have been proposed to achieve a partial automation of the Matchoperation for specific application domains. We present a taxonomy that covers many of the existingapproaches, and we describe these approaches in some detail. In particular, we distinguish betweenschema- and instance-level, element- and structure-level, and language- and constraint-based match-ers. Based on our classification we review some previous match implementations thereby indicatingwhich part of the solution space they cover. We intend our taxonomy and review of past work to beuseful when comparing different approaches to schema matching, when developing a new matchalgorithm, and when implementing a schema matching component.

Multivariate matching and bias reduction in the surgical outcomes study.

Abstract: Background Outcomes studies often need a level of detail that is not present in administrative data, therefore requiring abstraction of medical charts. Case-control methods may be used to improve statistical power and reduce abstraction costs, but limitations of exact matching often preclude the use of many covariates. Unlike exact matching, multivariate matching may allow cases to be matched simultaneously on hundreds of covariates. Objectives To develop multivariate matched case-control pairs in a study of death after surgery in the Medicare population. Research design Using 830 randomly selected index cases of patients who died within 60 days from admission, controls were found who did not die within that time period, matching on risk for death and other patient characteristics with up to 173 variables used simultaneously in the matching algorithms. Subjects General and orthopedic Medicare surgical cases in Pennsylvania from 1995 to 1996. Controls were either selected from across the entire state (108,765 possible subjects), or from within the same hospital as the case. Measures Percent bias reduction and the average difference between cases and controls in units of standard deviations. Results Matched controls were far more similar to cases (deaths) upon admission to the hospital than typical patients, both in statewide and within hospital matches. Bias reduction was usually greater than 50% and often approached 100%. The difference between cases and matched controls for most variables was usually below 0.2 SD. Conclusions Multivariate matching methods may aid in conducting studies with Medicare claims records by improving the quality of matches, thereby achieving a better understanding of the etiology of outcomes.

Using matching estimators to evaluate alternative youth employment programs: Evidence from France, 1986–1988

Abstract: In this paper we apply the statistical framework recently proposed by (Imbens 1999) and (Lechner 1999) to identify the causal effects of multiple treatments under the conditional independence assumption. We show that under this assumption, matching with respect to the ratio of the scores allows to estimate nonparametrically the average conditional treatment effect for any pair of treatments. Consequently it is possible to estimate this effect by implementing non-parametric matching estimators, which were recently studied by Heckman, Ichimura, Smith and Todd (1998) and (Heckman, Ichimura and Todd (1998)). The application concerns the youth employment programs which were set up in France during the eighties to improve the labour market prospects of the most disadvantaged and unskilled young workers. The empirical analysis makes use of nonexperimental longitudinal micro data collected by INSEE (Institut National de la Statistique et des Etudes Economiques, Paris) from 1986 to 1988.

Gale-Shapley Stable Marriage Problem Revisited: Strategic Issues and Applications

Abstract: We study strategic issues in the Gale-Shapley stable marriage model. In the first part of the paper, we derive the optimal cheating strategy and show that it is not always possible for a woman to recover her women-optimal stable partner from the men-optimal stable matching mechanism when she can only cheat by permuting her preferences. In fact, we show, using simulation, that the chances that a woman can benefit from cheating are slim. In the second part of the paper, we consider a two-sided matching market found in Singapore. We study the matching mechanism used by the Ministry of Education (MOE) in the placement of primary six students in secondary schools, and discuss why the current method has limited success in accommodating the preferences of the students, and the specific needs of the schools (in terms of the "mix" of admitted students). Using insights from the first part of the paper, we show that stable matching mechanisms are more appropriate in this matching market and explain why the strategic behavior of the students need not be a major concern.

Non-standard inferences in description logics

Abstract: Description Logics.- Non-Standard Inferences.- Characterizing Subsumption.- LCS and MSC.- Matching.- Conclusion.

Matching the faces of robbers captured on video

Abstract: Recent research has shown that unfamiliar face matching from both high- and low-quality closed circuit television video images to photographs is highly prone to error, even when viewpoint and expression are matched as closely as possible. The current experiments made use of a filmed, staged reconstruction of a bank raid that was captured on CCTV and on high-quality broadcasting video. Experiment 1 tested the ability of members of the public to match actors captured on CCTV to photo-spreads containing similar-looking distractors. Further experiments, each testing different groups of subjects, investigated matching ability using both high-quality photographs (Experiment 2) and broadcast-quality video material (Experiment 3). Experiment 3 also investigated the effect of disguising hairstyle, and varied whether or not the target was present in the photo line-up. The results of these experiments confirm those of previous work, that matching the identity of unfamiliar faces is highly fallible, even when high-quality footage is used. Experiments 4 and 5 tested matching ability using two-alternative forced-choice and single-item verification tasks. Performance remained highly error-prone even with the simplest question asked. The legal implications of the results are discussed. Copyright © 2001 John Wiley & Sons, Ltd.

The Propensity Score: A Means to An End

Abstract: Propensity score matching is a prominent strategy to reduce imbalance in observational studies. However, if imbalance is considerable and the control reservoir is small, either one has to match one control to several treated units or, alternatively, discard many treated persons. The first strategy tends to increase standard errors of the estimated treatment effects while the second might produce a matched sample that is not anymore representative of the original one. As an alternative approach, this paper argues to carefully reconsider the selection equation upon which the propensity score estimates are based. Often, all available variables that rule the selection process are included into the selection equation. Yet, it would suffice to concentrate on only those exhibiting a large impact on the outcome under scrutiny, as well. This would introduce more stochastic noise making treatment and comparison group more similar. We assess the advantages and disadvantages of the latter approach in a simulation study.

System and method for optimizing search results

Abstract: A system and method for searching for documents identified in a database, wherein the method comprises the steps of establishing a first search criterion associated with a keyword match between a keyword entry and the identified documents, establishing at least one additional search criterion based on a document attribute of the identified documents, determining a criterion matching score for identified documents for each of the established search criteria, associating a scaling factor with each of the established search criteria, calculating an overall matching score for a selection of the identified documents from the criterion matching scores and scaling factors associated therewith, and ordering the selection of identified documents based upon the calculated overall matching scores.

System for providing ride matching services using e-mail and the internet

Abstract: An on-line ride sharing system employs a dynamic database of geographical information in map form together with information that is input into the system by individual users and potential users of the system. An analysis program is integrated with the database to evaluate applications filed by users, and to present a user with a map display of origin and destination locations of potential ride sharing partners. A communication route is provided by the system between the user and potential partners to allow the parties to maintain anonymity and privacy so long as is desired.

Apparatus and methods for providing personalized application search results for wireless devices based on user profiles

Abstract: An exemplary method for providing personalized application search results in a mobile device comprises the steps of receiving a search request from a user, the search request including at least one search keyword and a user identifier, searching an application registry database for a first set of matching applications based on the search keyword, searching an application selection table for a second set of matching applications based on the search keyword and the user identifier, ordering the second set of matching applications based on frequency of use parameters in the application selection table to obtain an ordered second set of matching applications, appending a set of application in the first set of matching applications but not in the second set of matching applications to the end of the ordered second set of matching applications, generating a response to the search request based on the third set of matching applications, and sending the response to the user.