{"title":"Quality guidelines for mixed methods research in intervention studies","authors":"Gizela Kopač, V. Hlebec","doi":"10.51936/mysp2698","DOIUrl":"https://doi.org/10.51936/mysp2698","url":null,"abstract":"Among researchers' many investigations of the use of mixed methods in intervention studies, more recent discussions especially concern the roles played in such studies by qualitative research, intervention phases, procedures, and integration (Gallo and Lee, 2016; Woolcock, 2018; O'Cathain, 2018; Creswell and Plano Clark, 2018). One can find the basic procedures to follow while realizing a mixed methods experimental design (Creswell and Plano Clark, 2018), practical guidance (O'Cathain, 2018) for using qualitative research with a randomized control trial (RCT), and a mixed methods appraisal tool for appraising the methodological quality of RCTs, non-randomized studies, and mixed methods – MMAT (Hong et al., 2018). However, no model exists to assess the quality of mixed methods research in intervention studies, particularly experimental and quasi-experimental research in complex interventions. Our aim is to develop such a theoretical model. Today, the number of interventions relying on mixed methods methodology is growing exponentially. A theoretical model is called for to help assess the quality of mixed methods research in intervention studies, and in this respect our aim is to: (1) provide an overview of guidelines, recommendations, models, and quality criteria for mixed methods research; (2) overview the guidelines for intervention studies; (3) give a summary of guidelines and models for mixed methods research in such studies; (4) evaluate the mentioned guidelines, models, and quality criteria; (5) identify and describe the key elements of these guidelines, models, and quality criteria; and (6) develop a theoretical model for assessing the quality of mixed methods research designs used in intervention studies.","PeriodicalId":242585,"journal":{"name":"Advances in Methodology and Statistics","volume":"157 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128823768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Limiting spectral distribution of large dimensional random matrices of linear processes","authors":"Zahira Khettab","doi":"10.51936/zjbw7680","DOIUrl":"https://doi.org/10.51936/zjbw7680","url":null,"abstract":"The limiting spectral distribution (LSD) of large sample radom matrices is derived under dependence conditions. We consider the matrices (X_{N}T_{N}X_{N}^{prime}) , where (X_{N}) is a matrix ((N times n(N))) where the column vectors are modeled as linear processes, and (T_{N}) is a real symmetric matrix whose LSD exists. Under some conditions we show that, the LSD of (X_{N}T_{N}X_{N}^{prime}) exists almost surely, as (N rightarrow infty) and (n(N)/N rightarrow c > 0). Numerical simulations are also provided with the intention to study the convergence of the empirical density estimator of the spectral density of (X_{N}T_{N}X_{N}^{prime}).","PeriodicalId":242585,"journal":{"name":"Advances in Methodology and Statistics","volume":"10 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120946570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Cibulková, Z. Šulc, H. Řezanková, Sergej Sirota
{"title":"Associations among similarity and distance measures for binary data in cluster analysis","authors":"J. Cibulková, Z. Šulc, H. Řezanková, Sergej Sirota","doi":"10.51936/yelx5179","DOIUrl":"https://doi.org/10.51936/yelx5179","url":null,"abstract":"The paper focuses on similarity and distance measures for binary data and their application in cluster analysis. There are 66 measures for binary data analyzed in the paper in order to provide a comprehensive insight into the problematics and to create their well-arranged overview. For this purpose, formulas by which they were defined are studied. In the next part of the research, the results of object clustering on generated datasets are compared, and the ability of measures to create similar or identical clustering solutions is evaluated. This is done by using chosen internal and external evaluation criteria, and comparing the assignments of objects into clusters in the process of hierarchical clustering. The paper shows which similarity measures and distance measures for binary data lead to similar or even identical results in hierarchical cluster analysis.","PeriodicalId":242585,"journal":{"name":"Advances in Methodology and Statistics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123884710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recent decline in life expectancy at birth in Slovenia","authors":"Aleša Lotrič Dolinar, Jože Sambt","doi":"10.51936/nyzs2168","DOIUrl":"https://doi.org/10.51936/nyzs2168","url":null,"abstract":"For many decades, life expectancy at birth (e0) in Slovenia has been increasing at a very rapid pace. However, in 2015, e0 declined slightly; it recovered in 2016, but fell again in 2017 for women. In the same period, a pause in declining mortality was observed in numerous developed countries worldwide. It is too early to provide a thorough analysis and firm conclusions, but we shed some light on the topic by decomposing the observed decline in Slovenia by age and cause of death. In particular, using a life table model and life expectancy decomposition technique, we analyse what cause of death for what age group contributed the most to this decline in life expectancy at birth. We show that the main reason for the recent drop in life expectancy at birth in Slovenia was higher mortality due to external causes for men of all ages and due to neoplasms for women above 60 years and men above 50 years.","PeriodicalId":242585,"journal":{"name":"Advances in Methodology and Statistics","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117112658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Home team advantage in the English Premier League","authors":"P. Marek, F. Vávra","doi":"10.51936/kuie7054","DOIUrl":"https://doi.org/10.51936/kuie7054","url":null,"abstract":"The home team advantage in association football is a well known phenomenon. The aim of this paper is to offer a different view on the home team advantage. Usually, in association football, every two teams—team A and team B—play each other twice in a season. Once as a home team and once as a visiting, or away team. This gives us two results between teams A and B which are combined together to evaluate whether team A, against its opponent B, recorded a result at its home ground—in the comparison to the away ground—that is better, even, or worse. This leads to a random variable with three possible outcomes, i.e. with trinomial distribution. The combination and comparison of home and away results of the same two teams is the key to eliminate problems with different squad strengths of teams in a league. The bayesian approach is used to determine point and interval estimates of unknown parameters of the source trinomial distribution, i.e. the probability that the result at home will be better, even, or worse. Moreover, it is possible to test a hypothesis that the home team advantage for a selected team is statistically significant.","PeriodicalId":242585,"journal":{"name":"Advances in Methodology and Statistics","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133699013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measuring personal networks with surveys","authors":"T. Kogovsek, V. Hlebec","doi":"10.51936/tvlq6671","DOIUrl":"https://doi.org/10.51936/tvlq6671","url":null,"abstract":"Like in other fields of inquiry in the social sciences, in social network research the most frequently used measurement method is the survey. Compared with other measurement objects such as networks of opinions, attitudes or values, measurement is more complex and thus often more challenging. Measurement typically occurs in two main phases. First, network units are measured (generated). Second, the relationships among the units and other unit characteristics (e.g. demographic properties) are determined, while some specific questions arise as to whether whole or egocentric (personal) networks are to be measured. In this paper, we limit ourselves to measuring personal networks, especially when compared with different methods for generating networks. There are five basic approaches to generating a personal network: name generator, role generator, event generator, positional generator, and contextual generator. Each is associated with particular research goals, costs (financial, time, respondent burden), advantages, and limitations. Moreover, the complexity and specifics of generating networks mean one must consider the characteristics of data collection modes (e.g. face-to-face, telephone, web). In this sense, we will present the advantages and limits of various methods of generating personal networks, evaluate them critically and comparatively, and illustrate them with often used examples.","PeriodicalId":242585,"journal":{"name":"Advances in Methodology and Statistics","volume":"1149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126707142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Pavlova, I. Gumennikov, Evgeny Monastyrny, E. Golubeva
{"title":"Wellbeing assessment yardstick","authors":"I. Pavlova, I. Gumennikov, Evgeny Monastyrny, E. Golubeva","doi":"10.51936/gleo6116","DOIUrl":"https://doi.org/10.51936/gleo6116","url":null,"abstract":"Although Russia manifests some dynamics in its national policy on ageing, it still lacks comprehensive tools for the older generation wellbeing assessment both on national and regional levels. This research work is an ongoing project aimed at the development of the composite index (composite indicator) to assess the elderly population wellbeing in Russia for cross-regional comparison to equip Russian policy-makers with an essential tool and relevant reliable data to facilitate the decision-making and policy design at national, regional and local levels. The paper discusses the possibility of selecting relevant data from the pool of the official state statistics indicators to assess the elderly generation's wellbeing in 85 regions of the Russian Federation by four index domains (economic, social, health and regional environment dimensions). Due to a high geographical and territorial heterogeneity, this index can be advised to be adopted as a potential tool to monitor wellbeing across Russian regions with the focus on policy development for macro-regions. This grouping of regions can minimize transaction costs of bargaining on behalf of the 85 regions while developing national policies and strategies. The paper employs the Russian Elderly Wellbeing Index (REWI) to compare calculation results for 2014 and 2016 as well as addresses the issue of elderly population wellbeing analysis on the meso level in the context of federal districts. The authors run cluster analysis for the REWI indicators to compare clusters of Russian regions and federal districts.","PeriodicalId":242585,"journal":{"name":"Advances in Methodology and Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130051650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Danica Fink-Hafner, T. Dagen, May Doušak, Meta Novak, Mitja Hafner-Fink
{"title":"Delphi method","authors":"Danica Fink-Hafner, T. Dagen, May Doušak, Meta Novak, Mitja Hafner-Fink","doi":"10.51936/fcfm6982","DOIUrl":"https://doi.org/10.51936/fcfm6982","url":null,"abstract":"The paper presents the Delphi method and tests its usefulness when searching for a consensus on definitions, especially in a particular social science field. Based on an overview of the characteristics and uses of the Delphi method, a special Delphi design for searching for minimal common definitions of globalisation, Europeanisation and internationalisation in higher education and their mutual relationships is presented in detail. While the method proved valuable, its strengths and weaknesses are also discussed. Finally, ideas for adjusting the Delphi method are proposed.","PeriodicalId":242585,"journal":{"name":"Advances in Methodology and Statistics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121132260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"bad mathematics of the bad luck theory","authors":"Mariia Beliaeva","doi":"10.51936/uemw1852","DOIUrl":"https://doi.org/10.51936/uemw1852","url":null,"abstract":"The mathematics of the Bad Luck theory of carcinogenesis by Tomasetti and Vogelstein generated a great deal of controversy among cancer specialists but did not draw the mathematicians' attention. Thus the gross mathematical mistakes of the theory foundation did not get a proper critique and remained unnoticed. As a result, the sensational quantitative estimates of the role of Bad Luck in cancer occurrence, though being erroneous, have spread widely among researchers and the general public and got the unfair popularity. The present paper reviews the actual mathematical mistakes of Bad Luck theory.","PeriodicalId":242585,"journal":{"name":"Advances in Methodology and Statistics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114115206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Estimating Bayes factors from minimal summary statistics in repeated measures analysis of variance designs","authors":"Thomas J. Faulkenberry","doi":"10.51936/abic6583","DOIUrl":"https://doi.org/10.51936/abic6583","url":null,"abstract":"In this paper, I develop a formula for estimating Bayes factors directly from minimal summary statistics produced in repeated measures analysis of variance designs. The formula, which requires knowing only the F-statistic, the number of subjects, and the number of repeated measurements per subject, is based on the BIC approximation of the Bayes factor, a common default method for Bayesian computation with linear models. In addition to providing computational examples, I report a simulation study in which I demonstrate that the formula compares favorably to a recently developed, more complex method that accounts for correlation between repeated measurements. The minimal BIC method provides a simple way for researchers to estimate Bayes factors from a minimal set of summary statistics, giving users a powerful index for estimating the evidential value of not only their own data, but also the data reported in published studies.","PeriodicalId":242585,"journal":{"name":"Advances in Methodology and Statistics","volume":"517 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133464562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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