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01 May 2019Volume 7 Issue 5 Previous Issue    Next Issue

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Randomization Tests for Experimental Data Using R LÜ Xiaokang, FU Yingtao Psychology: Techniques and Application. 2019, 7 (5):  266-275.  DOI: 10.16842/j.cnki.issn2095-5588.2019.05.001 Abstract ( 1274 )   PDF（pc） (1529KB) ( 890 )   Save Randomization tests are based on the randomization distribution of one chosen statistic derived from all the possible random assignment results of experimental treatments to determine experimental effects. Compared with the statistical inference based on sampling distribution, which derived from resampling from one well defined population, randomization tests do not need the assumption of population normality, and thus is a more appropriate inference framework for randomized experiments, especially in the case of small sample size or when outliers exist. With the free and open source software R and its powerful packages, randomization tests of mean differences as well as other statistics for two or more treatments can be applied efficiently. But it still needs further promotion in the education process and application of psychological statistics. Related Articles | Metrics

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Procedure of Power Analysis and a Multilevel Analysis Example ZHAO Li, WANG Hui Psychology: Techniques and Application. 2019, 7 (5):  276-283.  DOI: 10.16842/j.cnki.issn2095-5588.2019.05.002 Abstract ( 615 )   PDF（pc） (665KB) ( 998 )   Save Factors that can affect power could be design factors, instrumental factors, and statistical factors. The power analysis is important to a study. To be more specific, the priori power analysis can help researchers to determine the necessary number of participants needed to detect the differences between treatments, which can help researchers save money and efforts, before a study has been conducted. In addition, a post-hoc power analysis could help researchers evaluate the experimental design, which is helpful for the future use. There are some problems in the application of power analysis. It is hard to conduct the power analysis when the research or the design is complicated. In addition, there are some misinterpretations of the analysis results. Furthermore, there are limit numbers and features of software that can conduct power analysis. One example of conducting a multilevel power analysis has been shown with Optimal Design. The teaching of power analysis has been recommended to undergraduate and graduate students. Researchers should also get the importance of the application of power analysis to optimize the experimental design and improve the reliability of research results. Related Articles | Metrics

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Calculating Confidence Intervals of Cohens d and Eta-squared: A Practical Primer rWANG Jun, SONG Qiongya, XU Yuepei, JIA Binbin, HU Chuanpeng, Psychology: Techniques and Application. 2019, 7 (5):  284-296.  DOI: 10.16842/j.cnki.issn2095-5588.2019.05.003 Abstract ( 1773 )   PDF（pc） (1131KB) ( 1219 )   Save The recent replication crisis in psychology has motivated many researchers to reform the methods they used in research, reporting effect sizes (ES) and their confidence intervals (CIs) becomes a new standard in mainstream journals. However, a practical tutorial for calculating CIs is still lacking. In this primer, we introduced theoretical basis of CIs of the two most widely-used effect size, Cohen's d and η2, in plain language. The CIs of both Cohen's d and η2 are calculated under the condition that the alternative hypothesis (H1) is true, and both rely on the estimation of non-centrality parameters of non-central distributions by using iterative approximations. More specifically, non-central t-distribution for Cohen's d and non-central F-distribution  for η2. Then, we illustrated how to calculate them in R and JASP with real data. This practical primer may help Chinese psychological researchers understand the CIs better and report CIs in their own research. Related Articles | Metrics

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Multi-site Collaboration Approaches to Replicable Research in the Psychological and Brain Sciences KONG Xiangzhen Psychology: Techniques and Application. 2019, 7 (5):  297-304.  DOI: 10.16842/j.cnki.issn2095-5588.2019.05.004 Abstract ( 463 )   PDF（pc） (993KB) ( 553 )   Save The replicability issue has received increased attention over recent years in a variety of fields including psychology and neuroscience. Two plausible roots have been considered contributing to this issue: intrinsic problems in traditional statistical methods, and potential problematic research practices in the traditional studies. Multiple calls for reproducible and replicable researches have been proposed. Multi-site collaboration approaches could play a critical role in this progress. As the new generations of scientists, young researchers may want to pursue open science and multi-site collaboration approaches for conducting replicable research in the psychological and brain sciences. Related Articles | Metrics

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A Study on Narrative Construction Characteristics of Self-identity of Secondary Vocational Students Based on Life Story Paradigm CHEN Yuxi Psychology: Techniques and Application. 2019, 7 (5):  305-312.  DOI: 10.16842/j.cnki.issn2095-5588.2019.05.005 Abstract ( 317 )   PDF（pc） (781KB) ( 641 )   Save Narration is mainly about storytelling, which runs through the past, present and future of the individual, and provides a reasonable and perfect theoretical system for the formation of self identity. Based on the paradigm of life story research, this study studied the narrative characteristics of 75 secondary vocational students with different self-identity status by using the life story interview technique. The results indicated that: a. The low level of the secondary vocational students in overall narrative construction, and there are significant differences in narrative themes between urban and rural students. b. The narrative construction characteristics are differ from various self-identity status, The higher level of self-identity, the more positive narrative tone and the higher level of self-growth. After all, The higher the level of self-identity of secondary vocational students, the more positive of the life narrative tone, and the more they can reflect on themselves from the story and obtain the positive development and growth. Related Articles | Metrics

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Review of Domestic Research on Flow at Work:Concept, Antecedents and Consequences DAI Bao, LUO Rui Psychology: Techniques and Application. 2019, 7 (5):  313-320.  DOI: 10.16842/j.cnki.issn2095-5588.2019.05.006 Abstract ( 511 )   PDF（pc） (557KB) ( 1031 )   Save Flow at work is a short-term peak experience characterized by absorption, work enjoyment, and intrinsic work motivation. In this paper, the domestic literature about flow at work was analyzed systematically from three aspects: the meaning, the antecedents and the consequence. Results show that the antecedents of flow at work included personal factors(personality traits and values, motivations and attitudes, perceptions and emotions), job factors(job resources and job demands), and environmental factors(leadership styles, social relationship, organizational climate and changes); the consequences of flow at work included psychological outcomes(cognitive, emotional and attitudinal outcomes) and behavioral outcomes(job performances, innovative behavior). In the future, domestic scholars should pay more attention to diversify research objects and research methods, and test more antecedents and consequences of flow at work. Related Articles | Metrics