Recent Developments on Structural Equation Models

Montfort, C.A.G.M. van; Oud, Johan H. L.; Satorra, Albert

doi:10.1007/978-1-4020-1958-6

Cited by 13 publications

(3 citation statements)

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“…When using real-world data to verify and evaluate the theoretical model, χ 2 is susceptible to sample size. The larger the sample size, the more significant the results, and the easier to reject the theoretical model ( 55 ). The results of confirmatory factor analysis (CFA) showed that all the fitting indexes meet the requirements except for χ 2 / df [Root Mean Square Error of Approximation (RMSEA) = 0.064, Root Meansquare Residual (RMR) = 0.03, Normed Fit Index (NFI) = 0.99, Relative Fitting Index (RFI) = 0.98, Comparative Fit Index (CFI) = 0.99, Incremental Fit Index (IFI) = 0.99, Tucker–Lewis Fit Index (TLI) = 0.98, Parsimonious Goodness Fit Index (PGFI) = 0.56, Parsimonious Normed Fit Index (PNFI) = 0.68, Parsimonious Comparative Fit Index (PCFI) = 0.68], which indicated the structure validity is good.…”

Section: Methodsmentioning

confidence: 99%

The mediating role of incentives in association between leadership attention and self-perceived continuous improvement in infection prevention and control among medical staff: A cross-sectional survey

Wang

Zhang²,

Liu³

et al. 2023

Front. Public Health

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ObjectivesPromoting improvement in Infection Prevention and Control (IPC) is an important part of improving the quality of care. The influence of leadership attention and incentives on the self-perceived continuous improvement in IPC has drawn a lot of attention, but relevant academic research is still lacking. The objective of this study is to explore the effect of leadership attention on self-perceived continuous improvement in IPC among medical staff and its underlying mechanisms.MethodThe 3,512 medical staff from 239 health facilities in Hubei, China, were surveyed online during September 2020. Data on leadership attention, incentives, and improvement in Infection Prevention and Control were collected using self-administered questionnaires. Correlation analysis was used to analyze the relationship between leadership attention, incentives, and improvement in Infection Prevention and Control. Amos 24.0 was used to analyze the mediating role.ResultsThe scores of leadership attention, incentives and self-perceived continuous improvement in Infection Prevention and Control were all high. The score of leadership attention was the highest (4.67 ± 0.59), followed by self-perceived continuous improvement (4.62 ± 0.59) and incentives in Infection Prevention and Control (4.12 ± 0.83). Leadership attention positively affected self-perceived continuous improvement in Infection Prevention and Control (β = 0.85, 95% CI = [0.83, 0.87]). Moreover, incentives partially mediated the effect of leadership attention on self-perceived continuous improvement in Infection Prevention and Control among medical staff (β = 0.13, 95% CI = [0.12, 0.15]).ConclusionLeadership attention positively affects self-perceived continuous improvement in Infection Prevention and Control among medical staff, and incentives mediates this relationship. The present study has valuable implications for self-perceived continuous improvement in Infection Prevention and Control from the perspective of leadership attention and incentives.

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Section: Methodsmentioning

confidence: 99%

The mediating role of incentives in association between leadership attention and self-perceived continuous improvement in infection prevention and control among medical staff: A cross-sectional survey

Wang

Zhang²,

Liu³

et al. 2023

Front. Public Health

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“…In this study, the soil variables were recorded on the ordinal scale initially, thus we tried to adjust the scale through transformation. Unfortunately, the ordinal scale of the soil physical variables was inappropriate in SEM, which should be performed under the assumption of normality [12]. Therefore, jitter transformation was applied to change the scale from qualitative to quantitative by adding some noise as follows [24]:…”

Section: Methodsmentioning

confidence: 99%

“…Since frequent use of applications based on big data, several powerful analytical techniques have been developed for specific proposals. SEM has been carried out through two steps, which consists of measurement and structural parts [12,13]. First, the number of variables in the measurement part have effectively reduced to some common factors to prevent an excessive increase in the number of parameters.…”

Section: Introductionmentioning

confidence: 99%

Causality between climatic and soil factors on Italian ryegrass yield in paddy field via climate and soil big data

2019

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This study aimed to identify the causality between climatic and soil variables affecting the yield of Italian ryegrass (Lolium multiflorum Lam., IRG) in the paddy field by constructing the pathways via structure equation model. The IRG data (n = 133) was collected from the National Agricultural Cooperative Federation (1992–2013). The climatic variables were accumulated temperature, growing days and precipitation amount from the weather information system of Korea Meteorological Administration, and soil variables were effective soil depth, slope, gravel content and drainage class as soil physical properties from the soil information system of Rural Development Administration. In general, IRG cultivation by the rice-rotation system in paddy field is important and unique in East Asia because it contributes to the increase of income by cultivating IRG during agricultural off-season. As a result, the seasonal effects of accumulated temperature and growing days of autumn and next spring were evident, furthermore, autumnal temperature and spring precipitation indirectly influenced yield through spring temperature. The effect of autumnal temperature, spring temperature, spring precipitation and soil physics factors were 0.62, 0.36, 0.23, and 0.16 in order (p < 0.05). Even though the relationship between soil physical and precipitation was not significant, it does not mean there was no association. Because the soil physical variables were categorical, their effects were weakly reflected even with scale adjustment by jitter transformation. We expected that this study could contribute to increasing IRG yield by presenting the causality of climatic and soil factors and could be extended to various factors.

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‘Translation is not enough’: using the Global Person Generated Index (GPGI) to assess individual quality of life in Bangladesh, Thailand, and Ethiopia

Camfield

Ruta

2007

Qual Life Res

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Currently few subjective measures of Quality of Life (QoL) are available for use in developing countries, which limits their theoretical, methodological, and practical contribution (for example, exploring the relationship between economic development and QoL, and ensuring effective and equitable service provision). One reason for this is the difficulty of ensuring that translated measures preserve conceptual, item, semantic, operational, measurement; and functional equivalence (Herdman, M., FoxRushby, J., & Badia, X. (1998). Quality of Life Research, 7, 331), which is illustrated by an account of the translation, pre-piloting, and administration of a new individualised QoL measure, the Global Person Generated Index or 'GPGI'. The GPGI is based on the widely used Patient Generated Index (Ruta, Camfield, & Martin, (2004) Quality of Life Research, 13, 1545.) and offers many of the advantages of the participatory approaches commonly used in developing countries, with added methodological rigour, and quantitative outcomes. It was successfully validated in Bangladesh, Thailand, and Ethiopia, using quantitative and qualitative methods-open-ended, semi-structured interviews (SSIs), conducted immediately post-administration. Both the measure and method of 'qualitative validation' described later in the paper offer an exciting alternative for future researchers and practitioners in this field. The quantitative results suggest the GPGI shows cultural sensitivity, and is able to capture both the areas that are important to respondents, and aspects of life one would expect to impact on QoL in developing countries. There were strong correlation between scores from the GPGI and SSIs for the area of health, and moderate correlations for 'material wellbeing' (MWB)('Material wellbeing' refers to respondents' perceptions of their achievement in the areas of farming, debt reduction, assets, crops, livestock, job, land, property, and agriculture) and children. Weak to moderate correlations were observed between the Satisfaction with Life Scale and the GPGI; however, the highest coefficient was between the GPGI and the most conceptually similar item. Statistically significant differences were seen in GPGI scores between rich and poor, urban and rural respondents, and different countries. Health and material wellbeing scores, derived from the SSIs, also showed a linear relationship with GPGI scores, with a suggestion of curvilinearity at the higher levels, as predicted by a general QoL causal model. In conclusion, the GPGI has great potential for use in this area, especially when supported by extensive interviewer training, and supplemented with a cognitive appraisal schedule.

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Recent Developments on Structural Equation Models

Cited by 13 publications

References 0 publications

The mediating role of incentives in association between leadership attention and self-perceived continuous improvement in infection prevention and control among medical staff: A cross-sectional survey

The mediating role of incentives in association between leadership attention and self-perceived continuous improvement in infection prevention and control among medical staff: A cross-sectional survey

Causality between climatic and soil factors on Italian ryegrass yield in paddy field via climate and soil big data

‘Translation is not enough’: using the Global Person Generated Index (GPGI) to assess individual quality of life in Bangladesh, Thailand, and Ethiopia

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