Statistical Matching Research Articles

Dendroprovenancing: A preliminary assessment of potential to geo-locate kauri timbers in northern New Zealand

After 1840, New Zealand kauri (Agathis australis) became the focus of a large-scale timber industry in the upper North Island, which converted trees into timber that was then used in construction. Cities such as Auckland and Wellington relied on importing kauri to meet local demand for construction and other uses. Kauri timbers from buildings and in-ground features, mostly in Auckland city, have been collected for tree-dating and master chronology development. Although the use of timber at archaeological sites is understood, the geographic origin of the timber from within the natural range of kauri (north of 38 °S) is largely unknown. This limits interpretation of archaeological wood and constrains use of the tree-ring data in dendroclimatology. In this paper, we consider the potential to provenance kauri timbers used in 19th and early 20th century New Zealand buildings, using a combination of documentary sources, t-value mapping, and refined statistical matching using spatial patterns of correlations. Analysis of documentary sources for a test period of 1861–1865 CE indicates that there is sufficient information about the kauri timber industry to provide a geographic context for provenancing kauri in the upper North Island. The use of t-values for provenancing may be confounded by the relatively small size of the kauri growth region and a lack of sufficient spatial differentiation in growth patterns between the sub-regions. However, a new approach of using indexed residual chronologies and field correlations has promise for geo-locating timber in a relatively small region. The research highlights the value of establishing kauri provenance to New Zealand dendroclimatology, dendroarchaeology and environmental history.

What are the impacts of living in social housing? New evidence from Australia

In this paper, we apply statistical matching methods to a national longitudinal dataset of Australians facing housing insecurity to estimate the impacts of social housing on employment, education, health, incarceration and homelessness. We find social housing in Australia provides an important `safety net’ protecting people from homelessness. However, at least in the short run, individuals in social housing have similar outcomes in terms of employment, education, physical and mental health, and incarceration to other comparable individuals not in social housing. These are the first estimates of causal impacts of social housing, simultaneously estimating impacts on a range of shelter and non-shelter outcomes highlighted as important by the broader social housing literature. They also provide an interesting contrast with the existing US estimates. These results are potentially due to strict targeting of individuals into social housing and that they represent the average effect across individuals who may experience substantially different impacts.

Within study comparisons and risk of bias in international development: Systematic review and critical appraisal.

Many systematic reviews incorporate nonrandomised studies of effects, sometimes called quasi-experiments or natural experiments. However, the extent to which nonrandomised studies produce unbiased effect estimates is unclear in expectation or in practice. The usual way that systematic reviews quantify bias is through "risk of bias assessment" and indirect comparison of findings across studies using meta-analysis. A more direct, practical way to quantify the bias in nonrandomised studies is through "internal replication research", which compares the findings from nonrandomised studies with estimates from a benchmark randomised controlled trial conducted in the same population. Despite the existence of many risks of bias tools, none are conceptualised to assess comprehensively nonrandomised approaches with selection on unobservables, such as regression discontinuity designs (RDDs). The few that are conceptualised with these studies in mind do not draw on the extensive literature on internal replications (within-study comparisons) of randomised trials. Our research objectives were as follows:Objective 1: to undertake a systematic review of nonrandomised internal study replications of international development interventions.Objective 2: to develop a risk of bias tool for RDDs, an increasingly common method used in social and economic programme evaluation. We used the following methods to achieve our objectives.Objective 1: we searched systematically for nonrandomised internal study replications of benchmark randomised experiments of social and economic interventions in low- and middle-income countries (L&MICs). We assessed the risk of bias in benchmark randomised experiments and synthesised evidence on the relative bias effect sizes produced by benchmark and nonrandomised comparison arms.Objective 2: We used document review and expert consultation to develop further a risk of bias tool for quasi-experimental studies of interventions (ROBINS-I) for RDDs. Objective 1: we located 10 nonrandomised internal study replications of randomised trials in L&MICs, six of which are of RDDs and the remaining use a combination of statistical matching and regression techniques. We found that benchmark experiments used in internal replications in international development are in the main well-conducted but have "some concerns" about threats to validity, usually arising due to the methods of outcomes data collection. Most internal replication studies report on a range of different specifications for both the benchmark estimate and the nonrandomised replication estimate. We extracted and standardised 604 bias coefficient effect sizes from these studies, and present average results narratively.Objective 2: RDDs are characterised by prospective assignment of participants based on a threshold variable. Our review of the literature indicated there are two main types of RDD. The most common type of RDD is designed retrospectively in which the researcher identifies post-hoc the relationship between outcomes and a threshold variable which determines assignment to intervention at pretest. These designs usually draw on routine data collection such as administrative records or household surveys. The other, less common, type is a prospective design where the researcher is also involved in allocating participants to treatment groups from the outset. We developed a risk of bias tool for RDDs. Internal study replications provide the grounds on which bias assessment tools can be evidenced. We conclude that existing risk of bias tools needs to be further developed for use by Campbell collaboration authors, and there is a wide range of risk of bias tools and internal study replications to draw on in better designing these tools. We have suggested the development of a promising approach for RDD. Further work is needed on common methodologies in programme evaluation, for example on statistical matching approaches. We also highlight that broader efforts to identify all existing internal replication studies should consider more specialised systematic search strategies within particular literatures; so as to overcome a lack of systematic indexing of this evidence.

Serum and tissue proteomic signatures of patients with hepatocellular carcinoma using 2‑D gel electrophoresis

Hepatocellular carcinoma (HCC) accounts for ~85% of primary liver cancer cases and is a leading cause of mortality worldwide. Effective early diagnosis is difficult for HCC; however, effective biomarkers may be beneficial for diagnosis. In the current study, serum samples, and HCC and adjacent tissue samples were obtained from patients with HCC for the detection of biomarkers using 2-D gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time of flight (TOF)/TOF mass spectrometry. The crude serum samples did not need to be prepared for removal of high abundance proteins. The mRNA expression levels of HCC-associated proteins were detected in tissues using reverse transcription-quantitative PCR. Statistical analysis and database matching were used to identify the differentially expressed proteins detected in the serum and tissue groups. Immunohistochemistry (IHC) was performed to detect the expression of significant proteins in HCC and adjacent tissues. The results revealed ~800 protein spots on a 2-DE gel that were detected in serum samples, and 1,200 spots were identified in the tissue samples. The protein and mRNA expression levels of oxysterol binding protein-like 11 (OSBPL11) in HCC serum and tissue samples were consistent. Pathway analysis demonstrated that members of the apolipoprotein family, particularly apolipoprotein E (APOE), and RAS family members were closely associated in HCC, either directly or via ferratin heavy polypeptide 1. IHC results demonstrated that the APOE protein serves an important role in liver cancer development. The lysis buffer used in the current study was effective for serum protein separation in 2-DE sample preparation. In addition, the present study revealed that downregulated OSBPL11 may be a potential indicator for HCC, and the apolipoprotein family, particularly APOE, and the RAS family may cooperatively serve an important role.

Twitter user geolocation using web country noun searches

Several Web and social media analytics require user geolocation data. Although Twitter is a powerful source for social media analytics, its user geolocation is a nontrivial task. This paper presents a purely word distribution method for Twitter user country geolocation. In particular, we focus on the frequencies of tweet nouns and their statistical matches with Google Trends world country distributions (GTN method). Several experiments were conducted, using a recently created dataset of 744,830 tweets produced by 3298 users from 54 countries and written in 48 languages. Overall, the proposed GTN approach is competitive when compared with a state-of-the-art world distribution geolocation method. To reduce the number of Google Trends queries, we also tested a machine learning variant (GTN2) that is capable of matching the GTN responses with an 80% accuracy while being much faster than GTN.

Development of Coarse-Grained Models for Polymers by Trajectory Matching.

Coarse-grained (CG) models allow for simulating the necessary time and length scales relevant to polymers. However, developing realistic force fields at the CG level is still a challenge because there is no guarantee that the CG model reproduces all the properties of the atomistic model. A recent promising method was proposed for small molecules using statistical trajectory matching. Here, we extend this method to the case of polymeric systems. As the quality of the final model crucially depends on the model design, we study and discuss the effect of the modeling choices on the structure and dynamics of bulk polymers before a quantitative comparison is made between CG methods on different properties and polymers.

Statistical Review and Match Analysis of Rugby World Cups Finals.

The aim of this study was to describe the game related statistics and match analysis of rugby world cups finals from 1987 to 2015. Video recordings of all (n = 8 matches) rugby world cup finals were used for the purpose of this study. Games were analysed using the video analysis software (Sports code V8.9, Sportstec, Australia) and supplementary data were collected from the official reports published by the International Rugby Board and from webpages of Rugby World Cups. Magnitude of differences between the winners and losers was assessed mechanistically. Only 5 tries in total were scored in the last 8 rugby world cup finals. The main two modes of scoring points were penalty kicks and drop goals. Winning teams attempted more penalty kicks, yet seemed to miss more. The number of drop goals was similar between winning and losing teams. These findings highlight the significance of having an on form place-kicker and from a defensive perspective, conceding fewer penalties in kickable positions. Winners of the Rugby World Cup final won more scrums and lost few line-outs, emphasising the importance of winning the set-pieces. Further establishment of these variables and their influence on performance may be used to evaluate team performances and plan more effective tactical approaches to competition

Matching information from two independent informative samples

Statistical matching deals with the problem of how to combine information collected in different samples taken from the same target population, but on partly different survey variables. The purpose of this paper is to analyze the statistical matching problem under informative sampling designs, when applying the sample likelihood approach. First, a conditional independence assumption is made, which allows to define an identifiable population model under which the conditions guaranteeing the identifiability and estimability of the sample likelihood are investigated. Next, the uncertainty in statistical matching under informative sampling designs is discussed, with particular attention to the three-variate normal case. A simulation experiment illustrating the theoretical results is performed.

Glomerular Filtration Rate Estimation by a Novel Numerical Binning-Less Isotonic Statistical Bivariate Numerical Modeling Method

Statistical bivariate numerical modeling is a method to infer an empirical relationship between unpaired sets of data based on statistical distributions matching. In the present paper, a novel efficient numerical algorithm is proposed to perform bivariate numerical modeling. The algorithm is then applied to correlate glomerular filtration rate to serum creatinine concentration. Glomerular filtration rate is adopted in clinical nephrology as an indicator of kidney function and is relevant for assessing progression of renal disease. As direct measurement of glomerular filtration rate is highly impractical, there is considerable interest in developing numerical algorithms to estimate glomerular filtration rate from parameters which are easier to obtain, such as demographic and ‘bedside’ assays data.

Adolescent Pregnancy Prevention: Meta-Analysis of Federally Funded Program Evaluations.

Beginning in 2010, the US Department of Health and Human Services (HHS) funded more than 40 evaluations of adolescent pregnancy prevention interventions. The government's emphasis on rigor and transparency, along with a requirement that grantees collect standardized behavioral outcomes, ensured that findings could be meaningfully compared across evaluations. We used random and mixed-effects meta-analysis to analyze the findings generated by these evaluations to learn whether program elements, program implementation features, and participant demographics were associated with effects on adolescent sexual risk behavior. We screened all 43 independent evaluation reports, some of which included multiple studies, funded by HHS and completed before October 1, 2016. HHS released, and our team considered, all such studies regardless of favorability or statistical significance. Of these studies, we included those that used a randomized or high-quality quasi-experimental research design. We excluded studies that did not use statistical matching or provide pretest equivalence data on a measure of sexual behavior or a close proxy. We also excluded studies that compared 2 pregnancy prevention interventions without a control group. A total of 44 studies from 39 reports, comprising 51 150 youths, met the inclusion criteria. Two researchers extracted data from each study by using standard systematic reviewing and meta-analysis procedures. In addition, study authors provided individual participant data for a subset of 34 studies. We used mixed-effects meta-regressions with aggregate data to examine whether program or participant characteristics were associated with program effects on adolescent sexual risk behaviors and consequences. To examine whether individual-level participant characteristics such as age, gender, and race/ethnicity were associated with program effects, we used a 1-stage meta-regression approach combining participant-level data (48 635 youths) with aggregate data from the 10 studies for which participant-level data were not available. Across all 44 studies, we found small but statistically insignificant mean effects favoring the programs and little variability around those means. Only 2 program characteristics showed statistically reliable relationships with program effects. First, gender-specific (girl-only) programs yielded a statistically significant average effect size (P < .05). Second, programs with individualized service delivery were more effective than programs delivering services to youths in small groups (P < .05). We found no other statistically significant associations between program effects and program or participant characteristics, or evaluation methods. Nor was there a statistically significant difference in the mean effect sizes for programs with previous evidence of effectiveness and previously untested programs. Although several individual studies reported positive impacts, the average effects were small and there was minimal variation in effect sizes across studies on all of the outcomes assessed. Thus, we were unable to confidently identify which individual program characteristics were associated with effects. However, these studies examined relatively short-term effects and it is an open question whether some programs, perhaps with distinctive characteristics, will show longer-term effects as more of the adolescent participants become sexually active. Public Health Implications. The success of a small number of individualized interventions designed specifically for girls in changing behavioral outcomes suggests the need to reexamine the assumptions that underlie coed group approaches. However, given the almost total absence of similar programs targeting male adolescents, it is likely to be some time before evidence to support or reject such an approach for boys is available.

Improving Stylised Working Time Estimates with Time Diary Data: A Multi Study Assessment for the UK

Accurate working time estimates represent an important component of the statistical toolbox used for economics forecasting and policy-making. The relatively good availability of such estimates may sometimes induce researchers to take them for granted and see their reliability as largely unproblematic. There is however a growing body of evidence showing that measurement errors may affect their robustness and quality, especially as far as specific but policy relevant subgroups of the population such as part-time or atypical workers are concerned. Against this background, the goal of this paper is to investigate the reliability of paid weekly working-time measurement instruments commonly available in a key UK social survey, the Labour Force Survey. It focuses on the discrepancies between estimates obtained by self-assessed/aggregated instruments—also known as stylised—and those recorded using time diaries which have been found more truthful to the time spent working in ones paid job(s). It is also to explore ways to improve the reliability of stylised estimates in datasets for which no time diary instruments are available, contrasting those where ’usual’ and ’actual’ hours of work are recorded. It does so by creating calibration weights based on the Work Schedule recorded in the 2000 and 2015 UK Time Use Surveys and using them to up/down scale stylised estimates in the 2000 and 2015 UK Labour Force Survey using statistical matching. Such techniques could enable significant improvements of measurement errors in large scale social surveys at a minimal cost.

Statistical dynamical model to predict extreme events and anomalous features in shallow water waves with abrupt depth change

Understanding and predicting extreme events and their anomalous statistics in complex nonlinear systems are a grand challenge in climate, material, and neuroscience as well as for engineering design. Recent laboratory experiments in weakly turbulent shallow water reveal a remarkable transition from Gaussian to anomalous behavior as surface waves cross an abrupt depth change (ADC). Downstream of the ADC, probability density functions of surface displacement exhibit strong positive skewness accompanied by an elevated level of extreme events. Here, we develop a statistical dynamical model to explain and quantitatively predict the above anomalous statistical behavior as experimental control parameters are varied. The first step is to use incoming and outgoing truncated Korteweg-de Vries (TKdV) equations matched in time at the ADC. The TKdV equation is a Hamiltonian system, which induces incoming and outgoing statistical Gibbs invariant measures. The statistical matching of the known nearly Gaussian incoming Gibbs state at the ADC completely determines the predicted anomalous outgoing Gibbs state, which can be calculated by a simple sampling algorithm verified by direct numerical simulations, and successfully captures key features of the experiment. There is even an analytic formula for the anomalous outgoing skewness. The strategy here should be useful for predicting extreme anomalous statistical behavior in other dispersive media.

Quantifying habitat losses and gains made by U.S. Species Conservation Banks to improve compensation policies and avoid perverse outcomes

AbstractCompensation policies seek to counterbalance biodiversity losses caused by development; however, their effectiveness is rarely tested. We examined U.S. Species Conservation Banks (SCBs) in California, a compensation program initiated 30 years ago. We quantified the effect of 59 SCBs (15,350 ha) on habitat extent using statistical matching methods. SCBs averted a small, yet significant, amount of habitat loss (62 ha) between 2001 and 2011. However, unexpectedly, SCBs also averted significant habitat gains (1,424 ha). It is not possible to determine if losses averted by SCBs equaled losses caused by development for which credits were sold (because records of the latter do not exist), but estimated averted gains were 35 times greater than averted losses. To improve practice, SCBs must be designed to achieve outcomes that are additional and avoid crowding out other programs incentivizing statewide conservation goals.

Rapid handling of outliers in dense sampling descriptor correspondence fields

The sparse-to-dense approach is considered to be the standard method of capturing the long-range motion of small objects during large displacement optical flow. Despite progress in the matching and interpolation of this approach, little work has focused on improving the handling of outliers after dense sampling descriptor matching. We propose an improved grid-based statistical matching method that can quickly remove outliers without calculating backward flow. First, a multigrid statistical matching method is developed to remove the most outliers of the dense sampling descriptor correspondence field. Second, to improve the accuracy of outliers handling, the misjudgment match in the edge grid is corrected based on the statistical matching constraint. The results of extensive experiments on public optical flow datasets demonstrate the effectiveness of the proposed method.

Statistical Matching as a Supplement to Record Linkage: A Valuable Method to Tackle Nonconsent Bias?

AbstractRecord linkage has become an important tool for increasing research opportunities in the social sciences. Surveys that perform record linkage to administrative records are often required to obtain informed consent from respondents prior to linkage. A major concern is that nonconsent could introduce biases in analyses based on the linked data. One straightforward strategy to overcome the missing data problem created by nonconsent is to match nonconsenters with statistically similar units in the target administrative database. To assess the effectiveness of statistical matching in this context, we use data from two German panel surveys that have been linked to an administrative database of the German Federal Employment Agency. We evaluate the statistical matching procedure under various artificial nonconsent scenarios and show that the method can be effective in reducing nonconsent biases in marginal distributions, but that biases in multivariate estimates can sometimes be worsened. We discuss the implications of these findings for survey practice and elaborate on some of the practical challenges of implementing the statistical matching procedure in the context of linkage nonconsent. The developed simulation design can act as a roadmap for other statistical agencies considering the proposed approach for their data.

AES Impact Evaluation With Integrated Farm Data: Combining Statistical Matching and Propensity Score Matching

A large share of the Common Agricultural Policy (CAP) is allocated to agri-environmental schemes (AESs), whose goal is to foster the provision of a wide range of environmental public goods. Despite this effort, little is known on the actual environmental and economic impact of the AESs, due to the non-experimental conditions of the assessment exercise and several data availability issues. The main objective of the paper is to explore the feasibility of combining the non-parametric statistical matching (SM) method and propensity score matching (PSM) counterfactual approach analysis and to test its usefulness and practicability on a case study represented by selected impacts of the AESs in Emilia-Romagna. The work hints at the potentialities of the combined use of SM and PSM as well as of the systematic collection of additional information to be included in EU-financed project surveys in order to enrich and complete data collected in the official statistics. The results show that the combination of the two methods enables us to enlarge and deepen the scope of counterfactual analysis applied to AESs. In a specific case study, AESs seem to reduce the amount of rent-in land and decrease the crop mix diversity.

Thermosensitive Moxibustion Induces A Better Therapeutic Effect in the Treatment of Facial Paralysis Patients

To compare the effect difference between the thermosensitive moxibustion (TSM) and conventional mild moxibustion (CMM) at Yifeng (TE 17) plus acupuncture intervention in the treatment of facial paralysis patients. The prospective cohort study design was used in the present study. A total of 183 patients were divided into a thermosensitive moxibustion (regional heat penetrating, heat extending, warmer in deep-tissue, etc.) group (n＝132) and a CMM group (n＝51) according to the patients' subjective feeling to moxibustion stimulation of TE 17. After propensity score matching (PSM, a statistical matching technique of observational data) processing by using SPSS 19. 0 software, outcomes of 33 cases in the TSM group and 33 cases in the CMM group were analyzed. In the 1st course (10 days) of treatment, TSM was applied to TE 17 till the thermosensitive feelings disappeared for patients in the TSM group, or CMM employed to TE 17 for 45 min for patients in the CMM group, followed by manual acupuncture stimulation of Cuanzhu (BL 2), Yangbai (GB 14), Sibai (ST 2), Quanliao (SI 18), Jiache (ST 6), etc. on the affected side (shallow needling, uniform reinforcing-reducing needle-manipulation) for 30 min, once daily. In the 2nd course (10 days), only manual acupuncture was performed, the same acupoints were stimulated with the same methods used in the 1st course, and in combination with bilateral Zusanli (ST 36) which was stimulated with reinforcing-needling technique. The interval between the 2 courses was 2 days. The modified Portmann scale (for movements of eyebrow raising, eye closing, cheek bulging, pouting, teeth showing and nostril widening, and symetry during resting state) was used to evaluate the severity of the facial palsy before and after the treatment. After the treatment, the Portmann scores were significantly higher than those of their own pre-treatment in each of the two groups (P < 0.01), being markedly higher in the TSM group than in the CMM group (P < 0.01), suggesting a better therapeutic effect of TSM. The thermosensitive moxibustion is considerably superior to the conventional mild moxibustion in improving the symptoms of facial paralysis patients.

SINR Distributions for Robust MIMO TX-Power Minimization With Controlled Outage

We offer a simple and comprehensive alternative to existing robust network optimization methods as a solution to the long-standing problem of cellular network optimization under imperfect channel state information at the transmitter (CSIT) conditions. Specifically, instead of relying on a relaxation of statistical constraints into deterministic convex equivalents, as done in current literature and which leads to tradeoffs between robustness and optimality, we derive accurate models for the distributions of users’ signal-to-interference-plus-noise ratio (SINRs), conditioned on constraint-matching SINR estimates obtained under imperfect CSIT. Using these distributions, precise accounting and compensation for imperfection on CSIT, as well as statistical outage matching, can be achieved directly via the design of deterministic, instantaneous, and convex SINR constraints. Simulated comparison with the state of the art demonstrates the significant performance gain achieved by the proposed solution.

Multiscale impact of researcher mobility.

International mobility facilitates the exchange of scientific, institutional and cultural knowledge. Yet whether globalization and advances in virtual communication technologies have altered the impact of researcher mobility is a relevant and open question that we address by analysing a broad international set of 26 170 physicists from 1980 to 2009, focusing on the 10-year period centred around each mobility event to assess the impact of mobility on research outcomes. We account for secular globalization trends by splitting the analysis into three periods, measuring for each period the effect of mobility on researchers' citation impact, research topic diversity, collaboration networks and geographical coordination. In order to identify causal effects we leverage statistical matching methods that pair mobile researchers with non-mobile researchers that are similar in research profile attributes prior the mobility event. We find that mobile researchers gain up to a 17% increase in citations relative to their non-mobile counterparts, which can be explained by the simultaneous increase in their diversity of co-authors, topics and geographical coordination in the period immediately following migration. Nevertheless, we also observe that researcher's completely curtail prior collaborations with their source country in 11% of the cross-border mobility events. As such, these individual-level perturbations fuel multiscale churning in scientific networks, e.g. rewiring the connectivity of individuals and ideas and affecting international integration. Together these results provide additional clarity on the complex relationship between human capital mobility and the dynamics of social capital investment, with implications for immigration and national innovation system policy.

Why are African American Governors and U.S. Senators so Rare? Exploring White Voters’ Responses to African American Statewide Candidates

Despite making notable gains at the local level, very few African Americans have been elected to the high-profile statewide offices of governor or U.S. senator. Previous research offers little systematic evidence on the role of racial prejudice in the campaigns of African Americans trying to reach these offices for the first time. In this paper, I introduce a new data set designed to test whether African American candidates for these offices are penalized due to their race. Comparing all 24 African American challengers (non-incumbents) from 2000 to 2014 to white challengers from the same party running in the same state for the same office around the same time, I find that white challengers are about three times more likely to win and receive about 13 percentage points more support among white voters. These estimates hold when controlling for a number of potential confounding factors and when employing several statistical matching estimators. The results conflict with earlier studies that focus on a single gubernatorial contest or elections at the U.S. House level.