SPSS for Intermediate Statistics

Leech, Nancy L.; Barrett, Karen Caplovitz; Morgan, George A

doi:10.4324/9781410611420

Cited by 331 publications

(236 citation statements)

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“…The ratio of the highest variance (31.28) and lowest variance (13.60) was slightly more than 2 (2.33). Given how the SPSS calculated ANCOVA, the use of ANCOVA test was acceptable in this case (Field, 2009; Leech, Barrett, & Morgan, 2008). Results indicated that the interaction between vaccination status and HPV/HPV vaccine knowledge was not significant ( F = 2.03, p = .16).…”

Section: Resultsmentioning

confidence: 99%

Human Papillomavirus Vaccine Increases High-Risk Sexual Behaviors

Ratanasiripong

2014

The Journal of School Nursing

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In 2006, the first human pappilomavirus (HPV) vaccine was approved for females aged 9 to 26. However, the national HPV vaccination rate among young women has been low. Public concerns were raised in regard to the fact that HPV vaccination might encourage unsafe sex. This cross-sectional study examined the differences in sexual practices between college women who have and have not obtained the HPV vaccine. Participants were 209 vaccinees and 175 nonvaccinees. A web-based survey was used. Sexual practices (numbers of sexual partners in a lifetime and in the past 12 months, condom use, condom use frequency) were not significantly different between the two groups. Among the vaccinees, the numbers of sexual partners before and after vaccination was also not significantly different. School nurses are at the frontier to advise young girls/parents on HPV vaccination before the girls engage in sexual intercourse. They may utilize these findings to address the misunderstanding that HPV vaccination encourages unsafe sex.

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Section: Resultsmentioning

confidence: 99%

Human Papillomavirus Vaccine Increases High-Risk Sexual Behaviors

Ratanasiripong

2014

The Journal of School Nursing

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“…The total variance explained how the variance is divided among the possible components. For the present data set, the first two principal components explained more than 80 per cent of the variation (Leech et al, 2014). Table 4 projects that the first principal component explains 73.243 per cent of the variation, and the second principal component explained 10.943 per cent of the variation which shows the importance of principal components and leads to the construction of inclusive growth index.…”

Section: Resultsmentioning

confidence: 75%

Has Social Sector Development Catalysed the Inclusiveness of India’s Economic Growth?

Chadha

Chadda

2020

The Indian Economic Journal

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The study attempts to examine the impact of social sector development on inclusive growth in India. Ever since Independence, India’s encounter with gnawing poverty and stark deprivation, particularly of the weaker and the marginalised sections of society, cajoled India’s planners to moot the development policies with the sole objective of exacerbating growth with equity. That is why since the beginning of the planning era, the stress had been laid on strengthening and expanding the social sectors with the premise that it would boost the inclusive growth agenda, manifesting in equal access to employment and economic opportunities; equal participation in decision-making and reduction in poverty and inequality. In conformity with the objective of our study, we intend to gauge the effect and contribution of different components of social sector development in India, on inclusiveness of growth using time series data for the period of 1985–1986 to 2015–2016. It was found that the expenditure related to ‘social security and welfare’ contributes significantly towards inclusive growth in India while the expenditure incurred on ‘welfare of marginalised class’ and ‘rural development’ exudes negative association with inclusiveness of growth.

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“…34 It is called binary logistic regression model when the dependent variable is articulated in 2 categories and several categories of applying the explanatory variables. 35 Thus, the logistic regression model that was employed in this study is a binary logistic regression model, where the dependent variable is Y and independent one is X . To elucidate the model, the following logistic distribution function was employed 36-38…”

Section: Methodsmentioning

confidence: 99%

Determinant Variables for Women’s Participation in Soil and Water Conservation Practices in North Western Ethiopia: The Case of Shebel Berenta District (Woreda), East Gojjam Zone, Amhara National Regional State

Bayu

2020

Air, Soil and Water Research

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Soil erosion occurs throughout the world and is a very serious problem especially in dry land areas of Ethiopia. Rural inhabitants try to develop some erosion control measures to reduce the negative impacts; however, the role of the women is not known and deserves to be studied to understand how land degradation processes are mitigated. Hence, the main goal of this study is to identify the determinant variables of women’s participation in soil and water conservation (SWC) practices in Shebel Berenta Woreda of Amhara Region in Ethiopia as a study case. Mixed-research method with sequential explanatory research design was employed through survey questionnaire, interview, key informant interview, focus group discussion, and field observation as data collection methods since 2019. Descriptive statistics and a binary logistic regression model were used to analyze the collected quantitative data. The result showed a significant number of respondents (86.4%) frequently participate in SWC, while 14.6% do not. Among those participated in SWC, 55.6%, 18.85 %, and 42.8% were highly involved in terracing, vegetation cover, and compost preparation as a part of SWC practices, respectively. In addition, 50.4% has participated in decision making about SWC, while 49.6% had not any involvement. The binary logistic regression model analysis shows widowed women (adjusted odds ratio [AOR] = 0.23, 95% confidence interval [CI] = 0.001, 0.814, P = .038); are able to read and write (AOR = 0.164, 95% CI = 0.027, 0.995, P = .049); have secondary education and higher levels (AOR = 0.139, 95% CI = 0.022, 0.874, P = .035). Similarly, those who do not have farm land (AOR = 0.263, 95% CI = 0.072, 0.964, P = .044); their lands do not show soil erosion (AOR = .043, 95% CI = 0.006, 0.296, P = .001); have not discussions about SWC (AOR = 0.142, 95% CI = 0.021, 0.952, P = .044); not receiving any advice to apply them (AOR = 0.145, 95% CI = 0.030, 0.694, P = .016) were variables that determine women’s participation in SWC. Therefore, the local government should work on awareness transference, providing new technologies, and building complete infrastructures to achieve better results of SWC.

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SPSS for Intermediate Statistics

Cited by 331 publications

References 0 publications

Human Papillomavirus Vaccine Increases High-Risk Sexual Behaviors

Human Papillomavirus Vaccine Increases High-Risk Sexual Behaviors

Has Social Sector Development Catalysed the Inclusiveness of India’s Economic Growth?

Determinant Variables for Women’s Participation in Soil and Water Conservation Practices in North Western Ethiopia: The Case of Shebel Berenta District (Woreda), East Gojjam Zone, Amhara National Regional State

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