Methods for the detection of carelessly invalid responses in survey data

Curran, Paul

doi:10.1016/j.jesp.2015.07.006

Cited by 884 publications

(900 citation statements)

References 32 publications

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“…Invalid data can be caused by several factors. One of the reasons is a lack of effort of respondents to answer the questions [10]. It is not the cause of invalid item because the number 26, 27, and 28 as almost all respondents attempt to answer the question of items.…”

Section: Resultsmentioning

confidence: 99%

Development and validation of science process skills instrument in physics

Jalil

Herman

Ali

et al. 2018

J. Phys.: Conf. Ser.

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Abstract. Science process skills not only a learning approach but also as a result of learning. It is a basic skills in science and a tools of scientist to investigate the science phenomena. The focus of this research is to develop a valid and reliable of Science Process Skills Instrument (I-KPS). This research is Research and Development (R&D). The step of this research is theoretical construction, determination of assessment objectives, construction of items indicator, items construction, experts judgment, revising of instrument, the first field trial, revising of instrument, the second field trial, and finalization of instrument. The subject of field trail is 46 student of grade 10 of High School of 1 Bajeng, Gowa Regency. The instrument (I-KPS) specification are: (1) the type of item is essay test completed by scoring rubrics, (2) I-KPS could be assess science process skill for high school student, and (3) purpose of this I-KPS is cognitive test of science process skill. It is developed for measuring 6 (six) indicators of science process skills that is identification variable, hypothesizing, planning the experiment, predicting, communicating, and interpreting data. The content validity coefficient of I-KPS is 0.96. The result of empirical validation is 45 items are valid in topics of newton law, gravitational force, work and energy, momentum and impulse, and harmonic motion. The reliability coefficient of I-KPS is 0.935. The conclusion is I-KPS as valid and reliable instrument both theoretically and empirically.

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Section: Resultsmentioning

confidence: 99%

Development and validation of science process skills instrument in physics

Jalil

Herman

Ali

et al. 2018

J. Phys.: Conf. Ser.

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“…There are many methods available with the potential to identify various forms of LQD (see, Curran, 2016;DeSimone et al, 2015). Some of these methods involve the direct assessment of response quality, others involve unobtrusive observation of respondent behavior patterns, and others require the calculation of statistical indicators.…”

Section: Methods For Detecting Lqdmentioning

confidence: 99%

“…It is important to emphasize that not all screens are appropriate for use in all studies. The suitability of screening techniques depends on survey design and methodology (Curran, 2016;DeSimone et al, 2015;Dunn et al, in press). For example, time-based screens require survey administrators to measure the time required for each respondent to complete the survey.…”

Section: Selection Of Screening Techniquesmentioning

confidence: 99%

“…Some recently proposed screening techniques could not be included in the present analysis due to the nature of the sample and data. Guttman errors and IRT-informed response probabilities are gaining popularity (see, Curran, 2016;Niessen, Meijer, & Tendeiro, 2016). However, as these techniques are computed using various operationalizations of item difficulty and/or discrimination, they are most appropriate for use with unidimensional scales containing many items (Meijer, Monelaar, & Sijtsma, 1994).…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

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Dirty Data: The Effects of Screening Respondents Who Provide Low-Quality Data in Survey Research

2017

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The purpose of this study is to empirically address questions pertaining to the effects of data screening practices in survey research. This study addresses questions about the impact of screening techniques on data and statistical analyses. It also serves an initial attempt to estimate descriptive statistics and graphically display the distributions of popular screening techniques. Data were obtained from an online sample who completed demographic items and measures of character strengths (N = 307). Screening indices demonstrate minimal overlap and differ in the number of participants flagged. Existing cutoff scores for most screening techniques seem appropriate, but cutoff values for consistency-based indices may be too liberal. Screens differ in the extent to which they impact survey results. The use of screening techniques can impact inter-item correlations, inter-scale correlations, reliability estimates, and statistical results. While data screening can improve the quality and trustworthiness of data, screening techniques are not interchangeable. Researchers and practitioners should be aware of the differences between data screening techniques and apply appropriate screens for their survey characteristics and study design. Low-impact direct and unobtrusive screens such as self-report indicators, bogus items, instructed items, longstring, individual response variability, and response time are relatively simple to administer and analyze. The fact that data screening can influence the statistical results of a study demonstrates that low-quality data can distort hypothesis testing in organizational research and practice. We recommend analyzing results both before and after screens have been applied.

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“…Respondents who complete the survey in less than 2/5 the median time (3 min and 51 s) were excluded. Median time is used as a metric for identifying careless responses10 as it is expected that participants who finish the questionnaire too quickly were unable to provide the required attention to the survey in the short timeframe.…”

Section: Methodsmentioning

confidence: 99%

UK survey of non-medical use of prescription drugs (NMURx) as a valuable source of general population illicit drug use data

Rockhill

Black

et al. 2018

Postgraduate Medical Journal

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Purpose of studyThe aim of the study is to describe the prevalence of illicit drug use in England and Wales using data from the UK Survey of Non-Medical Use of Prescription Drugs (NMURx) programme and to compare against the well-established Crime Survey England and Wales (CSEW). The rationale is that recreational and illicit drug use is common, but the prevalence is difficult to estimate with personal interviewing methods.Study designWe compared two cross-sectional population surveys (NMURx, n=8903 and CSEW, n=20 685) with data regarding self-reported recreational drug use and demographics. NMURx is an online survey using non-probability sampling methodology with preset demographical quotas based on census data. CSEW surveys drug use via computer-assisted self-interviewing as part of a computer-assisted personal-interviewing crime survey.ResultsCannabis was the most frequently used drug regardless of demographics. Prevalence of drug use for specific substances was generally higher for males, younger ages and students. The relationship between income and drug misuse is less clear. Self-reported prevalence of drug use in the NMURx survey is consistently higher than CSEW (absolute difference 1%–3 % across substances and timescales) and persists after stratification for gender, age, student status and household income.ConclusionsThe NMURx survey has a broad reach of participants, and a sampling scheme that achieves external validity, compared with general population demographics. NMURx’s online format allows flexibility in items surveyed and in response to emerging trends. The self-reported drug use in the NMURx cohort is comparable, although slightly higher, than the CSEW estimates.

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Methods for the detection of carelessly invalid responses in survey data

Cited by 884 publications

References 32 publications

Development and validation of science process skills instrument in physics

Development and validation of science process skills instrument in physics

Dirty Data: The Effects of Screening Respondents Who Provide Low-Quality Data in Survey Research

UK survey of non-medical use of prescription drugs (NMURx) as a valuable source of general population illicit drug use data

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