Assignment: Thesis And Statistics – Psy

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Assignment: Thesis And Statistics – Psy

Assignment: Thesis And Statistics – Psy

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  1. You are told that the difference between Republicans and Democrats on liking of pizza resulted in a t-statistic of 3.46, with a p-value of .045. Explain this finding for someone who does not understand t-
  2. What is a limitation of t-tests? In other words, why can’t we always use them in experiments?
  3. How could we re-design the sample study presented in the slides (on differences between married and single people) to make it appropriate for a dependent-samples (repeated measures) t-test. Be specific in your answer.
  4.  find an empirical article that reports a t-test (HINT: look for experimental studies). I strongly suggest using the PsycArticles database. Take a screenshot of where that t-test is reported in the paper and paste the picture here. Then, interpret this result in everyday language.

References* Please

In recent years a number of well-known and apparently well-established findings have , resulting in what is commonly referred to as the replication crisis. The APA Publication Manual 6thEdition notes that “The essence of the scientific method involves observations that can be repeated and verified by others.” (p. 12). However, a systematic investigation of the replicability of psychology findings published in  revealed that over half of psychology findings do not replicate (see a related commentary in ). Even more disturbing, a  showed that 64% of studies had sample sizes so small that strong evidence for or against the null or alternative hypotheses did not exist. Indeed, Morey and Lakens (2016) concluded that most of psychology is statistically unfalsifiable due to small sample sizes and correspondingly low power (see ). Our discipline’s reputation is suffering. News of the replication crisis has reached the popular press (e.g., ,  ,  ,).

An increasing number of psychologists have responded by promoting new research standards that involve open science and the elimination of . The open science perspective is made manifest in the  for journal publications. These guidelines were adopted some time ago by the . More recently, the guidelines were adopted by American Psychological Association journals () and journals published by Elsevier (). It appears likely that, in the very near future, most journals in psychology will be using an open science approach. We strongly advise readers to take a moment to inspect the .

A key aspect of open science and the TOP guidelines is the sharing of data associated with published research (with respect to medical research, see point #35 in the ). This practice is viewed widely as highly important. Indeed, open science is recommended by . All Tri-Agency grants must include a data-management plan that includes plans for sharing: “Moreover, a 2017 editorial published in the New England Journal of Medicineannounced that the International Committee of Medical JournalEditorsbelieves there is  As of this writing, .

The increasing importance of demonstrating that findings are replicable is reflected in calls to make replication a requirement for the promotion of faculty (see details in ) and experts in open science are now refereeing applications for tenure and promotion (see details at the  and ). Most dramatically, in one instance, a paper resulting from a dissertation was retracted due to misleading findings attributable to Questionable Research Practices. Subsequent to the retraction, the Ohio State University’s Board of Trustees unanimously revoked the PhD of the graduate student who wrote the dissertation (). Thus, the academic environment is changing and it is important to work toward using new best practices in lieu of older practices—many of which are synonymous with Questionable Research Practices. Doing so should help you avoid later career regrets and subsequent . One way to achieve your research objectives in this new academic environment is . Replications are becoming more common and there are even websites dedicated to helping students conduct replications (e.g., ) and indexing the success of replications (e.g.,). You might even consider conducting a replication for your thesis (subject to committee approval).

As early-career researchers, it is important to be aware of the changing academic environment. Senior principal investigators may be  (see this student perspective in a  and ) and research on resistance to data sharing indicates that one of the barriers to sharing data is that researchers do not feel that they have knowledge of . This document is an educational aid and resource to provide students with introductory knowledge of how to participate in open science and online data sharing to start their education on these subjects.

Guidelines and Explanations

In light of the changes in psychology, faculty members who teach statistics/methods have reviewed the literature and generated this guide for graduate students. The guide is intended to enhance the quality of student theses by facilitating their engagement in open and transparent research practices and by helping them avoid Questionable Research Practices, many of which are now deemed unethical and covered in the ethics section of textbooks.

This document is an informational tool.

How to Start

In order to follow best practices, some first steps need to be followed. Here is a list of things to do:

  1. Get an Open Science account. Registration at  is easy!
  2. If conducting confirmatory hypothesis testing for your thesis, pre-register your hypotheses (see Section 1-Hypothesizing). The Open Science Foundation website has helpful  and  to get you going.
  3. Also, pre-register your data analysis plan. Pre-registration typically includes how and when you will stop collecting data, how you will deal with violations of statistical assumptions and points of influence (“outliers”), the specific measures you will use, and the analyses you will use to test each hypothesis, possibly including the analysis script. Again, there is a lot of help available for this.

Exploratory and Confirmatory Research Are Both of Value, But Do Not Confuse the Two

We note that this document largely concerns confirmatory research (i.e., testing hypotheses). We by no means intend to devalue exploratory research. Indeed, it is one of the primary ways that hypotheses are generated for (possible) confirmation. Instead, we emphasize that it is important that you clearly indicate what of your research is exploratory and what is confirmatory. Be clear in your writing and in your preregistration plan. You should explicitly indicate which of your analyses are exploratory and which are confirmatory. Please note also that if you are engaged in exploratory research, then Null Hypothesis Significance Testing (NHST) should probably be avoided (see rationale in  (2004) and ).

This document is structured around the stages of thesis work: hypothesizing, design, data collection, analyses, and reporting – consistent with the headings used by Wicherts et al. (2016).We also list the Questionable Research Practices associated with each stage and provide suggestions for avoiding them. We strongly advise going through all of these sections during thesis/dissertation proposal meetings because a priori decisions need to be made prior to data collection (including analysis decisions).

To help to ensure that the student has informed the committee about key decisions at each stage, there are check boxes at the end of each section.

How to Use This Document in a Proposal Meeting

  1. Print off a copy of this document and take it to the proposal meeting.
  2. During the meeting, use the document to seek assistance from faculty to address potential problems.
  3. Revisit responses to issues raised by this document (especially the Analysis and Reporting Stages) when you are seeking approval to proceed to defense.

Consultation and Help Line

Note that the Center for Open Science now has a help line (for individual researchers and labs) you can call for help with open science issues. They also have training workshops. Please see their  for details.

 

 

 

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