Handbooks are a great resource for locating best practices, research theories, names of authors, background material, overviews of topics, and good keyword terminology to use when you search databases for journal articles and other materials to inform and support your research.
The handbooks are arranged by shelved by call number and arelocated to the light of the door as you enter the CLIC. You cannot check out handbooks, however you can scan (free scanning if you use the digital scanner in the CLIC's computer lab) or photocopy them for 8 cents per page using the public printer in the CLIC and your Cavalier debit card
Recommended Books s
Grey Literature Sources in Education
Grey literature can be articles, podcasts, vidoes, etc.
Contact the CLIC Librarians if you don't have access to a database you are interested in.
If you need a copy of a dissertation that is not available online full text, you can use the Library's free Interlibrary Loan Service to try and obtain a copy.
In addition to the databases below, you can also locate dissertations that are distributed as open access dissertations by searching Google using the the title, author. or keyword although identifying a dissertation from the retrieved results is a bit challenging due to the lack of meta tagging.
The difference between Google and Google Scholar is that Google Scholar focuses on the scholarly literature available on the Internet.
Google, on the other hand, has a broader scope, and is looking for resources regardless of where they come from
Examples of types of bias:
Publication bias is the term for what occurs whenever the research that appearsin the published literature is systematically unrepresentative of the population of completed studies. Simply put, when the research that is readily available differs in its results from the results of all the research that has been done in an area. This threatens the validity of conclusions drawn from reviews of published scientific research.
Language bias selective inclusion of studies published in English
Availability bias selective inclusion of studies that are easily accessible to the researcher
Cost bias selective inclusion of studies that are available free (e.g. open access), low cost, or subscription-based (e.g. access paid for by institution/library and, thus, "free" to researcher
Familiarity bias selective inclusion of studies only from one’s own discipline
Outcome bias selective reporting by the author, e.g., author may not include all data or analysis for subgroups
Positive results bias, a type of publication bias, occurs when authors are more likely to submit, or editors accept, positive than null (negative or inconclusive) results. A related term, "the file drawer problem", refers to the tendency for negative or inconclusive results to remain unpublished by their authors.
Outcome reporting bias occurs when several outcomes within a trial are measured but are reported selectively depending on the strength and direction of those results.
Find Additional Studies for the LR
In addtion to the resources listed in the left column, also consider using these resources to locate studies for inclusion in a meta-
- Citation searching
- Contacting experts
- Handsearching for articles
- Grey literature
- Look for registries of ongoing studies
- Databases such as e.g. Business Source Complete, EconLit, or other discipline based databases
Software & Other Tools
Meta-Analysis Reporting Form
Manage Data with RefWorks Software
Questions? Monday - Friday 8am-5pm
Ask Your Curry Librarians
Need help finding information for a research project or have questions about borrowing library books? Contact us. We are happy to help with any questions about research or library services.
CALL: Kay Buchanan 434-982-2664
CALL: Carole Lohman 434-924-7040
EMAIL: Email the Curry Librarians
SKYPE: Contact the CLIC Librarians to schedule a date and time.
Presenter: Dr. Elizabeth Tipton, Teachers' College, Columbia University
DATE: July 8-10, 2013 (9AM-3PM with noon-1PM lunch break), CLIC, room 306 Bavaro Hall
Overview: This three-day short course will introduce participants to the basics of conducting a meta-analysis. We will begin with problem formulation, literature searching protocols (provided by Kay Buchanan, Librarian UVA), inclusion criteria, coding protocols and a discussion of methods for reducing publication bias. We will then discuss the basic meta-analysis methods -- fixed and random effects models, quantifying heterogeneity, meta-regression, and subgroup analyses -- and conclude with an introduction to advanced methods, including robust variance estimation (helpful when each paper contributes multiple effect sizes). Throughout students will work in teams on replicating a published meta-analysis using Stata (or R).