Journal articles: 'Non-probability sampling'

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Uprichard, Emma. "Sampling: bridging probability and non-probability designs." International Journal of Social Research Methodology 16, no. 1 (January 2013): 1–11. http://dx.doi.org/10.1080/13645579.2011.633391.

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Raina, SunilKumar. "External validity & non-probability sampling." Indian Journal of Medical Research 141, no. 4 (2015): 487. http://dx.doi.org/10.4103/0971-5916.159311.

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Yang, Keming, and Ahmad Banamah. "Quota Sampling as an Alternative to Probability Sampling? An Experimental Study." Sociological Research Online 19, no. 1 (February 2014): 56–66. http://dx.doi.org/10.5153/sro.3199.

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In spite of the establishment of probability sampling methods since the 1930s, non-probability sampling methods have remained popular among many commercial and polling agents, and they have also survived the embarrassment from a few incorrect predictions in American presidential elections. The increase of costs and the decline of response rates for administering probability samples have led some survey researchers to search for a non-probability sampling method as an alternative to probability sampling. In this study we aim to test whether results from a quota sample, believed to be the non-probability sampling method that is the closest in representativeness to probability sampling, are statistically equivalent to those from a probability sample. Further, we pay special attention to the effects of the following two factors for understanding the difference between the two sampling methods: the survey's topic and the response rate. An experimental survey on social capital was conducted in a student society in Northeast England. The results suggest that the survey topic influences who responded and that the response rate was associated with the sample means as well. For these reasons, we do not think quota sampling should be taken as an acceptable alternative to probability sampling.

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Berzofsky, Marcus, Rick Williams, and Paul Biemer. "Combining Probability and Non-Probability Sampling Methods: Model-Aided Sampling and the O*NET Data Collection Program." Survey Practice 2, no. 6 (September 1, 2009): 1–6. http://dx.doi.org/10.29115/sp-2009-0028.

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Berndt, Andrea E. "Sampling Methods." Journal of Human Lactation 36, no. 2 (March 10, 2020): 224–26. http://dx.doi.org/10.1177/0890334420906850.

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Knowledge of sampling methods is essential to design quality research. Critical questions are provided to help researchers choose a sampling method. This article reviews probability and non-probability sampling methods, lists and defines specific sampling techniques, and provides pros and cons for consideration. In addition, issues related to sampling methods are described to highlight potential problems.

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Kim, Kyu-Seong. "A Study of Non-probability Sampling Methodology in Sample Surveys." Survey Research 18, no. 1 (February 28, 2017): 1–29. http://dx.doi.org/10.20997/sr.18.1.1.

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Schillewaert, Niels, Fred Langerak, and Tim Duharnel. "Non-Probability Sampling for WWW Surveys: A Comparison of Methods." Market Research Society. Journal. 40, no. 4 (July 1998): 1–13. http://dx.doi.org/10.1177/147078539804000403.

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Tansey, Oisín. "Process Tracing and Elite Interviewing: A Case for Non-probability Sampling." PS: Political Science & Politics 40, no. 04 (October 2007): 765–72. http://dx.doi.org/10.1017/s1049096507071211.

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Baker, R., J. M. Brick, N. A. Bates, M. Battaglia, M. P. Couper, J. A. Dever, K. J. Gile, and R. Tourangeau. "Summary Report of the AAPOR Task Force on Non-probability Sampling." Journal of Survey Statistics and Methodology 1, no. 2 (September 26, 2013): 90–143. http://dx.doi.org/10.1093/jssam/smt008.

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Franco, Francesco, and Anteo Di Napoli. "Metodi di campionamento negli studi epidemiologici." Giornale di Tecniche Nefrologiche e Dialitiche 31, no. 3 (August 28, 2019): 171–74. http://dx.doi.org/10.1177/0394936219869152.

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Sampling methods in epidemiological studies Sampling allows researchers to obtain information about a population through data obtained from a subset of the population, with a saving in terms of costs and workload compared to a study based on the entire population. Sampling allows the collecting of high quality information, provided that the sample size is large enough to detect a true association between exposure and outcome. There are two types of sampling methods: probability and non-probability sampling. In probability sampling the subset of the population is extracted randomly from all eligible individuals; this method, as all subjects have a chance of being chosen, allows researchers to generalize the findings of their study. In non-probability sampling, some individuals have no chance of being selected, because researchers do not extract the sample from all eligible subjects of a population; the sample is probably non-representative, the effect of sampling error cannot be estimated, so that the study produces non-generalizable results. Examples of probability sampling methods are: simple random sampling, systematic sampling, stratified sampling, and clustered sampling. Examples of non-probability sampling methods are: convenience sampling, judgement sampling.

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Tyrer, Stephen, and Bob Heyman. "Sampling in epidemiological research: issues, hazards and pitfalls." BJPsych Bulletin 40, no. 2 (April 2016): 57–60. http://dx.doi.org/10.1192/pb.bp.114.050203.

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SummarySurveys of people's opinions are fraught with difficulties. It is easier to obtain information from those who respond to text messages or to emails than to attempt to obtain a representative sample. Samples of the population that are selected non-randomly in this way are termed convenience samples as they are easy to recruit. This introduces a sampling bias. Such non-probability samples have merit in many situations, but an epidemiological enquiry is of little value unless a random sample is obtained. If a sufficient number of those selected actually complete a survey, the results are likely to be representative of the population. This editorial describes probability and non-probability sampling methods and illustrates the difficulties and suggested solutions in performing accurate epidemiological research.

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Zhang, Meijian, and Hongwei Sun. "Regression learning with non-identically and non-independently sampling." International Journal of Wavelets, Multiresolution and Information Processing 15, no. 01 (January 2017): 1750007. http://dx.doi.org/10.1142/s0219691317500072.

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In this paper, we study the performance of kernel-based regression learning with non-iid sampling. The non-iid samples are drawn from different probability distributions with the same conditional distribution. A more general marginal distribution assumption is proposed. Under this assumption, the consistency of the regularization kernel network (RKN) and the coefficient regularization kernel network (CRKN) are proved. Satisfactory capacity independently error bounds and learning rates are derived by the techniques of integral operator.

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Robinson, Andrew P., and Thomas E. Burk. "Sequential sampling of normal and non-normal populations." Canadian Journal of Forest Research 28, no. 5 (May 1, 1998): 660–64. http://dx.doi.org/10.1139/x98-048.

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This paper reports a simulation-based exploration into the computation of point and interval estimates for data arising from sequential sampling of populations with a variety of underlying distributions. We conclude that the coverage probability of the standard frequentist confidence interval estimates is overstated. The effect of non-normal behavior in the underlying population upon the properties of the interval estimate varies, depending upon the severity and type of anomaly (skewness, kurtosis, etc). Sequential sampling of certain nonsymmetric distributions performed very poorly compared with simple random sampling. We assess other interval estimates that do not overstate the coverage probability if the underlying population is normal (Gaussian).

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Grafström, Anton, Lionel Qualité, Yves Tillé, and Alina Matei. "Size constrained unequal probability sampling with a non-integer sum of inclusion probabilities." Electronic Journal of Statistics 6 (2012): 1477–89. http://dx.doi.org/10.1214/12-ejs719.

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Miller, Peter G., Jennifer Johnston, Matthew Dunn, Craig L. Fry, and Louisa Degenhardt. "Comparing Probability and Non-Probability Sampling Methods in Ecstasy Research: Implications for the Internet as a Research Tool." Substance Use & Misuse 45, no. 3 (February 2010): 437–50. http://dx.doi.org/10.3109/10826080903452470.

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Murtiarso, I. Bagus Hernu, Yuliana Isma Graha, and Niko Alnabawi. "Analysis of the Role of Quality on Job Satisfaction in Management with Sampling Techniques." Aptisi Transactions on Management (ATM) 2, no. 1 (January 2, 2018): 28–36. http://dx.doi.org/10.33050/atm.v2i1.785.

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Basically in each management at the College has rules and procedures for writing a study, including in using the research population and sampling techniques to ensure its accuracy. In this study discusses the notion of population and the types of population in a study, sampling units and framework for sampling in Educational research, sample concepts along with the types of sampling, and complete reasons for using sampling and conducting census research. , various sampling methods that will be described as both probability sampling and non probability sampling, as well as explaining the reasons for determining the number of samples both theoretically and practically. So that with the existence of research on the population of research and sampling techniques with examples in the scope of management, it is expected that the samples used in this study actually represent the existing population so that the findings and conclusions obtained from the sampling are valid. Keywords: Research Population, Sampling Technique, Probability and Non Probability

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Zhou, Xiang-Jun, Lei Shi, and Ding-Xuan Zhou. "Non-uniform Randomized Sampling for Multivariate Approximation by High Order Parzen Windows." Canadian Mathematical Bulletin 54, no. 3 (September 1, 2011): 566–76. http://dx.doi.org/10.4153/cmb-2011-029-8.

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AbstractWe consider approximation of multivariate functions in Sobolev spaces by high order Parzen windows in a non-uniform sampling setting. Sampling points are neither i.i.d. nor regular, but are noised from regular grids by non-uniform shifts of a probability density function. Sample function values at sampling points are drawn according to probability measures with expected values being values of the approximated function. The approximation orders are estimated by means of regularity of the approximated function, the density function, and the order of the Parzen windows, under suitable choices of the scaling parameter.

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Morio, Jérôme. "Non-parametric adaptive importance sampling for the probability estimation of a launcher impact position." Reliability Engineering & System Safety 96, no. 1 (January 2011): 178–83. http://dx.doi.org/10.1016/j.ress.2010.08.006.

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Lawson, Nuanpan, and Chugiat Ponkaew. "New generalized regression estimator in the presence of non response under unequal probability sampling." Communications in Statistics - Theory and Methods 48, no. 10 (September 19, 2018): 2483–98. http://dx.doi.org/10.1080/03610926.2018.1465091.

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Muchsin, Denny Murdany. "Pengaruh Non-Probability Sampling Batubara terhadap Parameter Dry Ash Antara Certificate of Analysis Loading dan Unloading." KILAT 9, no. 1 (April 25, 2020): 1–8. http://dx.doi.org/10.33322/kilat.v9i1.722.

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Umpire test (referee test) may be conducted by the coal supplier based on the potential loss due to the difference Certificate of Analysis (COA) in both ports (loading and unloading). The purpose of the research was to determine a comparison of COA from non-probability sampling compiled with standard. The research method used quantitative methods by collecting COA data on both ports. These data on the receipt of coal was obtained from a coal-fired steam power plant (PLTU). A Sampling at both ports was conducted by the non-probability sampling method. The assumption was determined that the sample preparation and analysis process had complied with the American Standard Testing and Material (ASTM) standards. The ratio of ash (dry basis) in both COA to its average was processed statistically by taking confidence intervals with a confidence level of 95%. This research showed that the ratio was in the range of 10.213% up to 16.793%, exceeding precision 10% as required by ASTM D2234-16. Therefore, the comparison of COA data from non-probability sampling, could not be used as a reference for the doubt of the work of independent surveyors e.g. COA unloading, then it is technically that umpire test could not be conducted by such comparison.

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Gruszczyński, Marek. "On Unbalanced Sampling in Bankruptcy Prediction." International Journal of Financial Studies 7, no. 2 (June 5, 2019): 28. http://dx.doi.org/10.3390/ijfs7020028.

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The paper discusses methodological topics of bankruptcy prediction modelling—unbalanced sampling, sample bias, and unbiased predictions of bankruptcy. Bankruptcy models are typically estimated with the use of non-random samples, which creates sample choice biases. We consider two types of unbalanced samples: (a) when bankrupt and non-bankrupt companies enter the sample in unequal numbers; and (b) when sample composition allows for different ratios of bankrupt and non-bankrupt companies than those in the population. An imbalance of type (b), being more general, is examined in several sections of the paper. We offer an extended view of the relationship between the biased and unbiased estimated probabilities of bankruptcy—probability of default (PD). A common error in applications is neglecting the possibility of calibrating the PD obtained from a bankruptcy model to the unbiased PD that is population adjusted. We show that Skogsviks’ formula of 2013 coincides with prior correction known for the logit model. This, together with solutions for other binomial models, serves as practical advice for obtaining the calibration of unbiased PDs from popular bankruptcy models. In the final section, we explore sample bias effects on classification.

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Ho Han, Joong. "Does Lending by banks and non-banks differ? Evidence from small business financing." Banks and Bank Systems 12, no. 4 (November 27, 2017): 98–104. http://dx.doi.org/10.21511/bbs.12(4).2017.09.

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Non-bank loans to corporate businesses have shown a dramatic increase compared to bank loans. Despite the increasing importance of non-bank lending, the differences between loans made by different types of lenders are mostly unknown. To uncover the distinctions, the author investigates whether bank and non-bank financial institutions deal differently with information scarcity of small firms by introducing lender-borrower distance as a proxy for information availability. Using the National Survey of Small Business Finances (NSSBF) provided by the Federal Reserve Board, estimate the loan approval probability models after controlling for various borrower characteristics. The NSSBF data is collected by using stratified sampling to ensure sufficient numbers of observations for minority-owned firms. To circumvent potential bias due to the sampling method, the author follows the approach suggested by Wooldridge (1999) and estimates a weighted maximum likelihood estimation to adjust for sampling design. This paper establishes novel evidence supporting the notion that banks and non-bank financial institutions are different in their ability to deal with information scarcity. Bank loan approval probability decreases as distance to their borrowers increases, while its effect on non-bank loan approval probability is statistically insignificant, supporting the notion that non-bank lending is different from bank lending in dealing with information asymmetry.

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Lawson, Nuanpan, and Chugiat Ponkaew. "A new variance estimator for unequal probability sampling without replacement in the presence of non-response." Journal of Applied Science 18, no. 2 (December 3, 2019): 1–10. http://dx.doi.org/10.14416/j.appsci.2019.07.001.

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Nejadi, Siavash, Juliana Leung, and Japan Trivedi. "Characterization of Non-Gaussian Geologic Facies Distribution Using Ensemble Kalman Filter with Probability Weighted Re-Sampling." Mathematical Geosciences 47, no. 2 (July 22, 2014): 193–225. http://dx.doi.org/10.1007/s11004-014-9548-8.

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Gautier, Athénaïs, David Ginsbourger, and Guillaume Pirot. "Goal-oriented adaptive sampling under random field modelling of response probability distributions." ESAIM: Proceedings and Surveys 71 (August 2021): 89–100. http://dx.doi.org/10.1051/proc/202171108.

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In the study of natural and artificial complex systems, responses that are not completely determined by the considered decision variables are commonly modelled probabilistically, resulting in response distributions varying across decision space. We consider cases where the spatial variation of these response distributions does not only concern their mean and/or variance but also other features including for instance shape or uni-modality versus multi-modality. Our contributions build upon a non-parametric Bayesian approach to modelling the thereby induced fields of probability distributions, and in particular to a spatial extension of the logistic Gaussian model. The considered models deliver probabilistic predictions of response distributions at candidate points, allowing for instance to perform (approximate) posterior simulations of probability density functions, to jointly predict multiple moments and other functionals of target distributions, as well as to quantify the impact of collecting new samples on the state of knowledge of the distribution field of interest. In particular, we introduce adaptive sampling strategies leveraging the potential of the considered random distribution field models to guide system evaluations in a goal-oriented way, with a view towards parsimoniously addressing calibration and related problems from non-linear (stochastic) inversion and global optimisation.

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Nurdiani, Nina. "Teknik Sampling Snowball dalam Penelitian Lapangan." ComTech: Computer, Mathematics and Engineering Applications 5, no. 2 (December 1, 2014): 1110. http://dx.doi.org/10.21512/comtech.v5i2.2427.

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Field research can be associated with both qualitative and quantitative research methods, depending on the problems faced and the goals to be achieved. The success of data collection in the field research depends on the determination of the appropriate sampling technique, to obtain accurate data, and reliably. In studies that have problems related to specific issues, requiring a non-probability sampling techniques one of which is the snowball sampling technique. This technique is useful for finding, identifying, selecting and taking samples in a network or chain of relationships. Phased implementation procedures performed through interviews and questionnaires. Snowball sampling technique has strengths and weaknesses in its application. Field research housing sector become the case study to explain this sampling technique.

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Rissel, Chris, and Freidoon Khavarpour. "Cervical Screening in Iranian Migrants." Australian Journal of Primary Health 4, no. 1 (1998): 93. http://dx.doi.org/10.1071/py98011.

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The cervical screening status of small and geographically diverse migrant communities is particularly difficult to assess. Usual approaches to migrant research such as telephone surveys using ethnically identifiable names or cluster sampling might not be feasible. Snowball sampling, although sometimes criticised for problems of inference with non-probability samples, might be the only cost-effective and viable alternative. Snowball sampling is the method of choice by sociologists studying networks and group interactions and has been shown to yield similar estimates of attitudes and demographic characteristics as probability sampling methods (Rumbaut, Chavez, Moser, Pickwell, & Wishik, 1988; Welch, 1975).

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Harling, Guy, Andrew Copas, Soazig Clifton, Anne M. Johnson, Nigel Field, Pam Sonnenberg, and Catherine H. Mercer. "Effect of weighting for sampling and non-response on estimates of STI prevalence in the third British National Survey of Sexual Attitudes and Lifestyles (Natsal-3)." Sexually Transmitted Infections 96, no. 7 (March 27, 2020): 481–84. http://dx.doi.org/10.1136/sextrans-2019-054342.

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ObjectivesIn addition to researcher-designed sampling biases, population-representative surveys for biomarker measurement of STIs often have substantial missingness due to non-contact, non-consent and other study-implementation issues. STI prevalence estimates may be biased if this missingness is related to STI risk. We investigated how accounting for sampling, interview non-response and non-provision of biological samples affects prevalence estimates in the third National Survey of Sexual Attitudes and Lifestyles (Natsal-3).MethodsNatsal-3 was a multistage, clustered and stratified probability sample of 16–74 year-olds conducted between 2010 and 2012. Individuals were sampled from all private residential addresses in Britain; respondents aged 16–44 were further sampled to provide a urine specimen based on characteristics including self-reported sexual behaviours. We generated prevalence estimates and confidence intervals for six STIs in five stages: first without accounting for sampling or non-response, then applying inverse-probability weights cumulatively accounting for interview sampling, interview non-response, urine sampling and urine non-response.ResultsInterview non-completion occurred for 42.3% of interview-sampled individuals; urine non-completion occurred for 43.5% of urine-sampled individuals. Interview-sampled individuals, interview respondents, those selected for urine samples and those providing urine samples were each in turn slightly more at-risk for most STIs, leading to lower prevalence estimates after incorporating each set of weights. Researcher-controlled sampling had more impact than respondent-controlled response.ConclusionsAccounting for both sampling structures and willingness to interview or provide urine specimens can affect national STI prevalence estimates. Using both types of weights, as was done in Natsal-3, is important in reporting on population-based biomarker surveys.

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Hannie, Hannie, Ultach Enri, and Yuyun Umaidah. "ANALYSIS OF KARAWANG ONLINE SALES CUSTOMER SATISFACTION USING CUSTOMER SATISFACTION INDEX (CSI) METHOD." Jurnal Pilar Nusa Mandiri 16, no. 1 (March 15, 2020): 7–12. http://dx.doi.org/10.33480/pilar.v16i1.1111.

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Karawang is one of the industrial cities. Most industry players look at Karawang as a strategic city to run a business. Many products have been produced from Karawang. However, there are lack in promoting, marketing the product and expanding the marketing area. The analysis of consumer satisfaction in Karawang is to determine the satisfaction of Karawang consumers to the prospects of promising online sales. Service attributes can be included in increasing online sales at Karawang using the Customer Satisfaction Index (CSI) method. The result of the Customer Satisfaction Index (CSI) is 78.43% which means that overall consumers who live in Karawang and have been shopped online are satisfied with the development of online shopping. This research was conducted in Karawang. The data used are primary data and secondary data. The sampling method is a non-probability sampling method, while the non-probability sampling method used sampling purposes.

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Foddai, Alessandro, Tobias Floyd, John McGiven, Katherine Grace, and Sarah Evans. "Evaluation of the English bovine brucellosis surveillance system considering probability of disease introduction and non-random sampling." Preventive Veterinary Medicine 176 (March 2020): 104927. http://dx.doi.org/10.1016/j.prevetmed.2020.104927.

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Shao, Xiaoyi, Siyuan Ma, Chong Xu, and Qing Zhou. "Effects of sampling intensity and non-slide/slide sample ratio on the occurrence probability of coseismic landslides." Geomorphology 363 (August 2020): 107222. http://dx.doi.org/10.1016/j.geomorph.2020.107222.

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Ibrahim, Isra Dewi Kuntary, Raden Bagus Faizal Irany Sidharta, and Mohammad Najib Rodhi. "Hubungan Antara Job Insecurity Terhadap Stres Karyawan Pelaku Pariwisata Perhotelan Akibat Dampak Pandemi Covid-19 (Studi Pada Karyawan Golden Palace Hotel Lombok)." Jurnal Manajemen dan Keuangan 9, no. 2 (December 2, 2020): 223–37. http://dx.doi.org/10.33059/jmk.v9i2.2627.

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Penelitian ini bertujuan untuk melihat pengaruh secara signifikan Antara Job Insecurity Terhadap Stres Karyawan Pelaku Pariwisata Perhotelan Akibat Dampak Pandemi Covid-19 (Studi Pada Karyawan Golden Palace Hotel Lombok). Pengumpulan data menggunakan metode penentuan sampel adalah Non Probability Sampling yaitu sampling aksidental dengan total kuesioner yang terkumpul 85 orang. Metode penentuan sampel adalah Non Probability Sampling yaitu Sampling aksidental. Analisis dan pengujian hipotesis menggunakan Partial Least Square (PLS) dengan instrument penelitian menggunakan kuesioner melalui google form secara online. Hasil penelitian menunjukkan bahwa terdapat pengaruh positif dan signifikan job insecurity terhadap stres karyawan pelaku pariwisata perhotelan akibat dampak pandemi Covid-19. Pihak manajemen Golden Palace Hotel Lombok diharapkan dapat memperhatikan hasil dari penelitian ini khususnya berkaitan dengan job insecurity dengan tingkat sedang menurut penilaian responden pada masa pandemi ini, agar karyawan dapat tetap merasa aman dan tidak khawatir atas keberlanjutan karirnya. Diharapkan pula bagi pihak manajemen untuk mengelola stress karyawan agar selalu memberikan kinerja terbaiknya untuk perusahaan.

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Richardson, Esther, Margaret Good, Guy McGrath, and Simon J. More. "The Use of Geographic Information System (GIS) and Non-GIS Methods to Assess the External Validity of Samples Postcollection." Journal of Veterinary Diagnostic Investigation 21, no. 5 (September 2009): 633–40. http://dx.doi.org/10.1177/104063870902100507.

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External validity is fundamental to veterinary diagnostic investigation, reflecting the accuracy with which sample results can be extrapolated to a broader population of interest. Probability sampling methods are routinely used during the collection of samples from populations, specifically to maximize external validity. Nonprobability sampling (e.g., of blood samples collected as part of routine surveillance programs or laboratory submissions) may provide useful data for further posthoc epidemiological analysis, adding value to the collection and submission of samples. As the sample has already been submitted, the analyst or investigator does not have any control over the sampling methodology, and hence external validity as routine probability sampling methods may not have been employed. The current study describes several Geographic Information System (GIS) and non-GIS methods, applied posthoc, to assess the external validity of samples collected using both probability and nonprobability sampling methods. These methods could equally be employed for inspecting other datasets. Mapping was conducted using ArcView 9.1. Based on this posthoc assessment, results from the random field sample could provide an externally valid, albeit relatively imprecise, estimate of national disease prevalence, of disease prevalence in 3 of the 4 provinces (all but Ulster, in the north and northwest, where sample size was small), and in beef and dairy herds. This study provides practical methods for examining the external validity of samples postcollection.

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Shah, Sada Hussain. "The Innovative Semi-Analytical Screen Survey Tool and Intermittent Screen Review Sampling Method Used Amid COVID-19 Pandemic." Review of European Studies 13, no. 2 (May 12, 2021): 91. http://dx.doi.org/10.5539/res.v13n2p91.

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Hence the social life is changing and social interaction is amplified by technology. Therefore, social research would change its approach/es concomitantly. We are living in the age of technology where many people are interacting through social media generally referred to as a screen. Therefore, it is creating the need for innovative screen research methods to study and give meaning to screen interaction. Due to lock-down and restrictions on physical interaction during the COVID-19 pandemic, the screen interaction is intensified. Particularly the community-based organizations, businesses, and academia were observed prone towards using screen interaction approaches. Similarly an International Non-Governmental Organization hereinafter (INGO) in Erbil, Iraq. Started a Facebook page to interact with its beneficiaries to listen to their urgent needs and feedback to project activities. Based on that monitoring and evaluation unit observed a need to monitor screen interaction between organization and community. Hence, the innovative approaches of screen survey and screen sampling were identified. To conduct an intermittent screen survey it was important to select a relevant sampling method. In general, there are two schools of sampling in social sciences. Probability sampling and non-probability sampling. Under probability sampling, each individual has the right to be selected as a participant in a study. Under non-probability sampling, participants are selected based on certain criteria that are relevant to the domain of study. Both schools of sampling have many types and sub-types selected as per the specifications of a study. Therefore, the Intermittent Screen Review Sampling (ISRS) method was developed based on precedent theoretical work. The screen survey refers to the collection and analysis of responses of viewers of any specific social media page. Where respondents are not asked to participate or share their feelings or thoughts. Respondents voluntarily appear on the screen and interact with any post and reflect their thoughts. Henceforth, the surveyors collect these displayed thoughts intermittently, do some analytical work, and produce meaning out of these emojis, shares, memes, and comments. Quantitative and qualitative analyses were conducted within the context of the post/s shared by authorized person/s on a social media official page. Thereafter, the results were presented in quantities and narrations. This research paper is developed to communicate these innovative approaches of semi-analytical screen survey and intermittent screen review sampling at a wider level. This research would pave a way for further screen studies and innovations that are the needs of our screen generation.

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Waldner, François. "The T Index: Measuring the Reliability of Accuracy Estimates Obtained from Non-Probability Samples." Remote Sensing 12, no. 15 (August 3, 2020): 2483. http://dx.doi.org/10.3390/rs12152483.

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In remote sensing, the term accuracy typically expresses the degree of correctness of a map. Best practices in accuracy assessment have been widely researched and include guidelines on how to select validation data using probability sampling designs. In practice, however, probability samples may be lacking and, instead, cross-validation using non-probability samples is common. This practice is risky because the resulting accuracy estimates can easily be mistaken for map accuracy. The following question arises: to what extent are accuracy estimates obtained from non-probability samples representative of map accuracy? This letter introduces the T index to answer this question. Certain cross-validation designs (such as the common single-split or hold-out validation) provide representative accuracy estimates when hold-out sets are simple random samples of the map population. The T index essentially measures the probability of a hold-out set of unknown sampling design to be a simple random sample. To that aim, we compare its spread in the feature space against the spread of random unlabelled samples of the same size. Data spread is measured by a variant of Moran’s I autocorrelation index. Consistent interpretation of the T index is proposed through the prism of significance testing, with T values < 0.05 indicating unreliable accuracy estimates. Its relevance and interpretation guidelines are also illustrated in a case study on crop-type mapping. Uptake of the T index by the remote-sensing community will help inform about—and sometimes caution against—the representativeness of accuracy estimates obtained by cross-validation, so that users can better decide whether a map is fit for their purpose or how its accuracy impacts their application. Subsequently, the T index will build trust and improve the transparency of accuracy assessment in conditions which deviate from best practices.

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Mubin, Nuril, and Setyaningsih Setyaningsih. "Pengaruh Konten Radikal Terhadap Sikap Radikalisme (Analisis Berdasarkan Theory of Planned Behavior dari Ajzen dan Fishbein)." Personifikasi: Jurnal Ilmu Psikologi 11, no. 2 (November 27, 2020): 181–201. http://dx.doi.org/10.21107/personifikasi.v11i2.9104.

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ABSTRACTThis study aims to determine the effect of radical content on the attitude of radicalism (analysis based on the theory of planned behavior of Ajzen and Fishbein). This study uses a quantitative approach. The number of samples in this study were users of active social media and following radical content with a total of 393 people. Sampling using purposive sampling technique (non-probability sampling). The instruments in this study are the scale of radical content and the scale of radicalism. The analysis of the data used is simple linear regression using the 23.0 for windows SPSS (statistical product and service solution) program. The results of this study indicate that the influence of radical content on radicalism is determined. Based on F count of 806.47 and probability of probability 0,000 (0,000 0.05) which means that the hypothesis is accepted, therefore there is a positive influence of radical content on the attitude of radicalism. The amount of the contribution or effective contribution of the influence of radical content on radicalism attitudes is 67,3% while the remaining 32,7% is influenced by other factors not measured in this study. ABSTRAKPenelitian ini bertujuan untuk melihat pengaruh konten radikal terhadap sikap radikalisme (analisis berdasarkan Teori Planned Behavior dari Ajzen Fishbein). Penelitian ini menggunakan pendekatan kuantitatif. Sample dalam penelitian ini berjumlah 393 orang yang aktif mengikuti konten radikal di media sosial. Teknik sampling yaitu Purpusive sampling (non-probability sampling). Alat ukur dalam penelitian ini menggunakan skala konten radikal dan skala sikap radikalisme. Analisis data yang digunakan regresi linier, SPSS seri 23. Hasil dari penelitian ini adalah ada pengaruh positif konten radikal terhadap sikap radikalisme. Didasarkan pada hasil hitung F= 806,47 dan probabilitas 0.000 (0.000 0.05). Sumbangan efektif konten radikal terhadap sikap radikalisme sebesar 67,3 % sementara sisanya 32,7% dipengaruhi faktor lain.

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Cabras, Stefano. "A Dirichlet Process Prior Approach for Covariate Selection." Entropy 22, no. 9 (August 28, 2020): 948. http://dx.doi.org/10.3390/e22090948.

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The variable selection problem in general, and specifically for the ordinary linear regression model, is considered in the setup in which the number of covariates is large enough to prevent the exploration of all possible models. In this context, Gibbs-sampling is needed to perform stochastic model exploration to estimate, for instance, the model inclusion probability. We show that under a Bayesian non-parametric prior model for analyzing Gibbs-sampling output, the usual empirical estimator is just the asymptotic version of the expected posterior inclusion probability given the simulation output from Gibbs-sampling. Other posterior conditional estimators of inclusion probabilities can also be considered as related to the latent probabilities distributions on the model space which can be sampled given the observed Gibbs-sampling output. This paper will also compare, in this large model space setup the conventional prior approach against the non-local prior approach used to define the Bayes Factors for model selection. The approach is exposed along with simulation samples and also an application of modeling the Travel and Tourism factors all over the world.

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Gardi, J. E., J. R. Nyengaard, and H. J. G. Gundersen. "The proportionator: Unbiased stereological estimation using biased automatic image analysis and non-uniform probability proportional to size sampling." Computers in Biology and Medicine 38, no. 3 (March 2008): 313–28. http://dx.doi.org/10.1016/j.compbiomed.2007.11.002.

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Zhang, Ganqing, Yanghui Xiang, Huixin Guo, and Yonghong Nie. "Structural reliability and its sensitivity analysis based on the saddlepoint approximation-line sampling method by dichotomy of golden section." Engineering review 39, no. 1 (2019): 11–20. http://dx.doi.org/10.30765/er.39.1.2.

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In order to solve the structural reliability and its sensitivity of the implicit nonlinear performance function (PF) the advantages of the saddlepoint approximation (SA) and line sampling (LS) are merged. Also, the merits of dichotomy and the solution efficiency of the golden section method are combined to propose the saddlepoint approximation-line sampling (SA-LS) method based on the dichotomy of the golden section point. This is complicated and changeable in the non normal variable space, which is a very hot issue of the present international study. For each sample, it is quick to find its zeropoint in PF along the important line sampling direction by the previously mentioned dichotomy so that the structural failure probability can be transformed into the mean of a series linear PFs failure probability, and the reliability sensitivity is just the derivative or partial one of the probability with respect to the relational variables. Examples show that the SA-LS method based on the dichotomy of the golden section point is of high precision and fast velocity in analyzing the structural reliability and sensitivity of the implicit nonlinear PF that are complicated and changeable in the non-normal variable space.

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Raue, Andreas, Clemens Kreutz, Fabian Joachim Theis, and Jens Timmer. "Joining forces of Bayesian and frequentist methodology: a study for inference in the presence of non-identifiability." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1984 (February 13, 2013): 20110544. http://dx.doi.org/10.1098/rsta.2011.0544.

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Increasingly complex applications involve large datasets in combination with nonlinear and high-dimensional mathematical models. In this context, statistical inference is a challenging issue that calls for pragmatic approaches that take advantage of both Bayesian and frequentist methods. The elegance of Bayesian methodology is founded in the propagation of information content provided by experimental data and prior assumptions to the posterior probability distribution of model predictions. However, for complex applications, experimental data and prior assumptions potentially constrain the posterior probability distribution insufficiently. In these situations, Bayesian Markov chain Monte Carlo sampling can be infeasible. From a frequentist point of view, insufficient experimental data and prior assumptions can be interpreted as non-identifiability. The profile-likelihood approach offers to detect and to resolve non-identifiability by experimental design iteratively. Therefore, it allows one to better constrain the posterior probability distribution until Markov chain Monte Carlo sampling can be used securely. Using an application from cell biology, we compare both methods and show that a successive application of the two methods facilitates a realistic assessment of uncertainty in model predictions.

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Stehr, Mads, and Markus Kiderlen. "Improving the Cavalieri estimator under non-equidistant sampling and dropouts." Image Analysis & Stereology 39, no. 3 (November 25, 2020): 197–212. http://dx.doi.org/10.5566/ias.2422.

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Motivated by the stereological problem of volume estimation from parallel section profiles, the so-called Newton-Cotes integral estimators based on random sampling nodes are analyzed. These estimators generalize the classical Cavalieri estimator and its variant for non-equidistant sampling nodes, the generalized Cavalieri estimator, and have typically a substantially smaller variance than the latter. The present paper focuses on the following points in relation to Newton-Cotes estimators: the treatment of dropouts, the construction of variance estimators, and, finally, their application in volume estimation of convex bodies.Dropouts are eliminated points in the initial stationary point process of sampling nodes, modeled by independent thinning. Among other things, exact representations of the variance are given in terms of the thinning probability and increments of the initial points under two practically relevant sampling models. The paper presents a general estimation procedure for the variance of Newton-Cotes estimators based on the sampling nodes in a bounded interval. Finally, the findings are illustrated in an application of volume estimation for three-dimensional convex bodies with sufficiently smooth boundaries.

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Sajib, Anamul Haque. "Rejection Sampling Schemes for Simulating from Arbitrary Probability Densities." Dhaka University Journal of Science 68, no. 1 (January 30, 2020): 59–64. http://dx.doi.org/10.3329/dujs.v68i1.54604.

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Simulating random variates from arbitrary non-normalized probability densities, very often they do not have familiar forms, is an increasingly important requirement in many different fields, especially in Bayesian statistics. Accept-reject algorithm is one of the commonly used methods to simulate random variates from such densities but restriction on choosing proposal density under this framework (heavier tails than the target density) limits its applicability to a larger extent. On the other hand, Markov Chain Monte Carlo (MCMC) method can choose proposal density arbitrary which makes this method applicable to a larger class of target densities5. In addition to MCMC method, a more general widely used method known as ratio-of-uniforms (RoU) which requires only two uniform variates to simulate one variates from such densities. However, no empirical comparison among these methods for simulating random variates from such densities was seen in the literature. In this paper, we limit our study only to MCMC and RoU methods to simulate random variates from such densities. Following the generation of random variates from such densities using these two methods, we compare the performance of these two methods based on quality of the generated samples. Finally, we conclude that RoU method performs better than MCMC method as far as quality of the generated sample (randomness) and computational cost are concerned. Dhaka Univ. J. Sci. 68(1): 59-64, 2020 (January)

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Osama, Ahmed, Tarek Sayed, and Said Easa. "Framework for evaluating risk of limited sight distance for permitted left-turn movements: case study." Canadian Journal of Civil Engineering 43, no. 4 (April 2016): 369–77. http://dx.doi.org/10.1139/cjce-2015-0498.

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A reliability analysis framework is used to evaluate the risk of limited sight distance for permitted left-turn movements due to the presence of opposing left-turn vehicles. Two signalized intersection approaches in the city of Surrey were used as case studies for the framework. Geometric and traffic video data was collected and analyzed using a computer vision tool to extract the input variables probability distributions. The data was used in the reliability analysis where first-order and Importance Sampling methods were performed. The analysis showed that the probability of non-compliance was considerable at one approach due to its large left-turn lane offset. The analysis also showed that the probability of non-compliance increased substantially when the obstacle vehicle was a bus rather than a passenger car. Moreover, the time gap had a higher impact on the probability of non-compliance compared to speed. Strategies were suggested to overcome the high probability of non-compliance.

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Michaels, Stuart, Vicki Pineau, Becky Reimer, Nadarajasundaram Ganesh, and J. Michael Dennis. "Test of a Hybrid Method of Sampling the LGBT Population: Web Respondent Driven Sampling with Seeds from a Probability Sample." Journal of Official Statistics 35, no. 4 (December 1, 2019): 731–52. http://dx.doi.org/10.2478/jos-2019-0031.

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Abstract This article presents the results of a pilot feasibility study comparing two alternative recruitment approaches based on Respondent Driven Sampling using initial seeds selected from a US nationally representative panel, AmeriSpeak, to augment the number of lesbian, gay, bisexual, and transgender (LGBT) respondents to a short web survey on smoking, discrimination, and health. In the nomination condition after completing the survey both LGBT and non-LGBT seeds were invited to share the names and email address of up to four LGBT persons they knew. In the recruitment condition, seeds were given four unique PINs and links to the survey to distribute to LGBT persons. Both conditions were successful in producing new LGBT respondents. The recruitment condition was much more productive. LGBT seeds (and their recruits) were much connected to and willing to contact other LGBT people they knew to participate in a survey. Comparisons of characteristics and responses from the initial samples and the LGBT referrals as well as comparisons to LGB samples from a large national survey are presented. Results demonstrate the promise of this hybrid technique for increasing the number of LGBT respondents through referrals from an initial probability based sample.

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Huang, Man, Shi Gui Du, Zhan You Luo, and Xiao Ying Zhang. "Study on the Influencing Factors of Sampling Representativeness of Rock Joints." Applied Mechanics and Materials 170-173 (May 2012): 1301–5. http://dx.doi.org/10.4028/www.scientific.net/amm.170-173.1301.

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The non-uniformity feature of rock joints’ surface profiles is the main influencing factor of the sampling representativeness. In order to analyze the sampling representativeness of rock joints statistically, the joint roughness coefficient (JRC) of 18 pieces of natural slate rock structural plane samples with size from 100mm to 1000mm were measured. The results show that it is necessary to evaluate the representativeness of rock joints in engineering practice due to the large non-uniformity of JRC. The total variation of JRC for different measurement sections, sizes and samples indicates that the sampling representativeness can be evaluated by the average value and the distribution probability of JRC; moreover, the sampling representativeness should be considered the statistical law evaluation of JRC for the concrete size and sample, and offered the accurate standard in changing range.

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Putra, Yudha Baskoro, and Lise Asnur. "ANALISIS SUSUNAN MENU KANTIN KARYAWAN DI KYRIAD HOTEL BUMIMINANG PADANG." Jurnal BOSAPARIS: Pendidikan Kesejahteraan Keluarga 11, no. 1 (February 9, 2021): 14. http://dx.doi.org/10.23887/jjpkk.v11i1.31994.

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Penelitian ini berjudul.Analisis Susunan Menu Kantin Karyawan Di Kyriad Hotel Bumiminang Padang. Tujuan dari penelitian ini.adalah untuk menganalisis susunan menu di kantin karyawan Hotel Kyriad Hotel Bumiminang Padang. Adapun keluhan yang dapat ditemukan oleh peneliti adalah salah satunya yaitu cita rasa, tekstur,.warna yang kurang bervariasi.terhadap makanan yang dihidangkan di kantin karyawan Hotel Kyriad Bumi Minang Padang. Penelitian ini merupakan penelitian..deskriptif kuantitatif dengan metode survey Jumlah sampel.dalam penelitian ini adalah 66 responden. Cara pengambilan sampel.dengan menggunakan teknik non probability sampling. Jenis non probability sampling yang digunakan adalah sampling..jenuh. Data dikumpulkan menggunakan kuesioner atau angket dengan menggunakan skala.likert. Teknik analisis data dilakukan dengan menggunakan program computer..SPSS versi 20.00. Hasil penelitian ini menunjukkan.bahwa: Susunan menu..kantin karyawan Kyriad Hotel Bumiminang Padang berada padaakategori Baik dengan nilai persentase 27% yang artinya susunan menu di kantin karyawan Kyriad Hotel Bumiminang Padang sudah baik sesuai dengan keinginan danaaharapan dari karyawan Kyriad Hotel Bumiminang Padang.Kata kunci: Analisis,.Susunan.Menu, Kyriad Hotel Bumiminang Padang

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Fahruna, Yulyanti. "Servant Leadership dan Kepuasan Kerja terhadap Kinerja Karyawan di Lembaga Keuangan Non Bank Pontianak." Jurnal Ekonomi Bisnis dan Kewirausahaan 5, no. 3 (December 24, 2016): 179. http://dx.doi.org/10.26418/jebik.v5i3.19080.

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This research aims to assess and obtain empirical evidence by testing different response toward servant leadership, job satisfaction on the performance of employees in non bank financial institutions of Pontianak. Non probability sampling technique in the form of purposive sampling is applied. The study was conduct 100 respondents, consist of 50 employees of PT. Pegadaian (Persero) Area Pontianak and 50 employees of PT. Finansia Multi Finance Pontianak. The result shows that among PT. Pegadaian (Persero) Area Pontianak and PT. Finansia Multi Finance Pontianak there is a difference in case of servant leadership, job satisfaction and performance of employees where as the similarity between both non bank financial institutions on Pontianak.

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Putra, Anak Agung Gede Alit Pramana, and Gerianta Wirawan Yasa. "Profitabilitas, Kepemilikan Manajerial, Kebijakan Dividen dan Nilai Perusahaan." E-Jurnal Akuntansi 31, no. 8 (August 26, 2021): 2142. http://dx.doi.org/10.24843/eja.2021.v31.i08.p20.

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The purpose of this study is to provide empirical evidence regarding the effect of financial and non-financial ratios on firm value. This research was conducted on a building construction sub-sector company on the Indonesia Stock Exchange (IDX). The number of samples taken was 32 observational samples, with non-probability sampling method, especially the sampling technique, namely purposive sampling. Data collection is done by non-participant observation. The analysis technique used is multiple linear regression analysis technique. The results of the analysis show that profitability, managerial ownership and dividend policy have a positive effect on the value of the building construction sub-sector companies on the Indonesia Stock Exchange in the 2016-2019. Keywords: Firm Value; Profitability; Managerial Ownership; Dividend.

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Tamene, Kaleb Amanu, and Bizuayehu Daba. "A Comparative Assessment on the Role of Private Investment in Poverty Reduction in Illubabor and Jimma Zones,Oromiya National Regional State, Ethiopia." International Journal of Multicultural and Multireligious Understanding 7, no. 2 (April 5, 2020): 552. http://dx.doi.org/10.18415/ijmmu.v7i2.1528.

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The research was assessing the role of private investment in poverty reduction in Jimma and Illibabor zones comparatively. There was almost little study was done in this areas and the research intended to fill such hole. For this purpose, necessary and careful literature reviews were done before. This research is workout by using a qualitative approach of research methodology and as far as the sampling technique concerned, we employed non probability sampling technique. From non probability sampling, purposive sampling technique was chosen. To this effect, Jimma and Illuababor Zones were purposively selected because of their prominence to Jimma university and which helps to save time and to implement one of the well known axiom of JU and that is “we are in the community” to promote the livelihoods of the community. Finally, the data gathered by using primary and secondary sources and the results proved that private investment is very important for the alleviatiation of poverty. For sure, there is a complementary relationship between private investment and poverty reduction. Moreover, the study finally recommends that Jimma and Illubabor zones should seriously work in creating enabling environment for private investment.

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Sholeh, Maimun. "PENGARUH SIKAP UNTUK KELUAR DARI KEMISKINAN TERHADAP KEBERDAYAAN MASYARAKAT MISKIN." Jurnal Ekonomi dan Pendidikan 16, no. 1 (July 3, 2020): 34–41. http://dx.doi.org/10.21831/jep.v16i1.32901.

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Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh sikap masyarakat miskin untuk keluar dari kemiskinan terhadap keberdayaan masyarakat miskin khususnya masyarakat miskin yang diberdayakan oleh lembaga zakat sehingga bisa dibuat strategi yang tepat untuk meningkatkan keberdayaan mereka. Penelitian ini merupakan studi eksplanatori dilakukan dengan menggunakan pendekatan SEM (Structural Equation Model). Anggota sampel ditentukan dengan metode non-probability sampling khususnya dengan purposive sampling. Data dikumpulkan secara cross section dianalisis secara kuantitatif. Dalam penelitian ini dapat disimpulkan bahwa sikap untuk keluar dari kemiskinan berpengaruh positif dan signifikan terhadap keberdayaan.Abstract: This study aims to decide the effect of the attitude of the poor to get out of poverty on the empowerment of the poor, especially the poor who are empowered by zakat institutions so that proper strategies can be made to increase their empowerment. This research is an explanatory study conducted using the SEM (Structural Equation Model) approach. The sample members are determined by the non-probability sampling method especially with purposive sampling. Data collected by cross-section were analyzed quantitatively. In this study it can be concluded that the attitude to get out of poverty has a positive and significant effect on empowerment.

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Journal articles on the topic 'Non-probability sampling'

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