Statistics and Design

Evaluators should know statistics, to analyze program data, for example, and also design.  These are just a few of the available links. First, here are links about doing statistical analysis. The second section shows links on research design.

Statistics books, guides

HyperStat  http://davidmlane.com/hyperstat/index.html   HyperStat Online is an introductory-level hypertext statistics book.  Also comprehensive links to other on line stat books and links to some stat jokes.
 

Statistics at square one   http://www.bmj.com/statsbk/      From BMJ, an on line brief stat text.  Also see Epidemiology for the uninitiated   http://www.bmj.com/epidem/epid.html


Electronic Textbook  http://www.statsoft.com/textbook/stathome.html   Complete on line statistics text book, with many advanced topics.
  

PA 765 Statnotes: An Online Textbook, by G. David Garson   http://faculty.chass.ncsu.edu/garson/PA765/statnote.htm   On line stats book, but with chapters on evaluation, surveys, sampling, some theoretical frameworks.
 

Statistics: power from data   http://www.statcan.gc.ca/edu/power-pouvoir/toc-tdm/5214718-eng.htm   general on line stat book with chapters about data collection, processing, problems, presenting, analyzing.
 

Timeweb    http://www.bized.co.uk/timeweb/    sort of an on line stat text.  Main topics include sections on: Digging for data. Where can you find it? What does it mean, etc?;  Crunching or processing the data; and Polishing or finishing the data.
 

A New View of Statistics   http://www.sportsci.org/resource/stats/contents.html   all the usual topics, but pretty comprehensive.   Another version is here,   http://www.sportsci.org/resource/stats/index.html   showing a table of contents on a left panel.

Statistical Good Practice Guidelines - Overview   http://www.rdg.ac.uk/ssc/publications/guides.html    Several booklets are available from this site, including Concepts Underlying The Design of Experiments , Confidence and Significance: Key Concepts of Inferential Statistics , Modern Approaches to the Analysis of Experimental Data and Modern Methods of Analysis   They are geared toward agricultural research but seem useful for any social scientist. 
 
 

Betty Jung's Statistics page   http://www.bettycjung.net/Statsites.htm     has links to many stat notes, such as
Stat Primer    http://www.sjsu.edu/faculty/gerstman/StatPrimer/    an on line public domain stat manual.
 

Respect for data    http://www.uiowa.edu/~soc/datarespect/data_training_frm.html      written and compiled by Ben Earnhart.  This is a guide on avoiding basic errors when making data sets, running analyses.
 

Methods for evaluating area-wide and organisation-based interventions in health and health care: a systematic review 1999.   http://www.hta.ac.uk/execsumm/summ305.htm   This report describes a systematic review of methods for evaluating cluster-based interventions.  It also evaluates existing practice in healthcare evaluation.  It is also a handbook for design.
 

The Little Handbook of Statistical Practice   http://www.tufts.edu/~gdallal/LHSP.HTM   basic stats to anova and regression.
 

Steve's Attempt to teach statistics   http://www.childrens-mercy.org/stats/   Has a short list of topics, which are useful, and also see Training opportunities at Children's Mercy Hospital for some class notes.

 
SticiGui: Statistics Tools for Internet and Classroom Instruction with a Graphical User Interface   http://www.stat.berkeley.edu/users/stark/SticiGui/   includes a text book on basics and advanced basics.


The North Carolina Center for Public Health Preparedness Training Website  http://nccphp.sph.unc.edu/training/   has free on line training for biostatistics, epidemiology, other topics.

 
Free Statistical Tools on the Web http://gsociology.icaap.org/methods/statontheweb.html    brief review of free statistical resources.  A short version of this article first appeared in the International Statistical Association newsletter, Vol 26, Number 1 (76),  2002, and is at   http://isi.cbs.nl/NLet/NLet021-04.htm   and    http://isi.cbs.nl/FreeTools.htm 


A Literature Review of the Use of Random Assignment Methodology in Evaluations of US Social Policy Programmes   http://www.dwp.gov.uk/asd/asd5/ih-index.asp   In house report #94


Criteria for evaluating an experimental design   http://www.utmem.edu/prevmed/pm/publications.html   see M4c_lecture_notes_2007_2008.pdf   Describes different types of designs and ad/disadvantages of each.

Experimental design   http://www.authorstream.com/User-Presentations/physioactive/   on line lecture slide show. By Chee-Wee Tan. See the show called week 2 experimental design.


Safety Science Monitor, Guide to Evaluating the Effectiveness of Strategies for Preventing Work Injuries   http://www.monash.edu.au/muarc/ipso/safebk.html   See chapters 3 and 4 on design.


 

Design, validity, Randomized Control Trials (RCT)


Research Methods Knowledge Base, chapter on design  http://www.socialresearchmethods.net/kb/design.htm


Allpsych on line texts   http://allpsych.com/onlinetexts.html   the research methods text is mainly about design. Also has an on line text on stats. For example, this    http://allpsych.com/researchmethods/quasiexperimentaldesign.html   is a brief overview of quasi experimental design.


Government of Canada Human Resources lists this:  http://www.hrsdc.gc.ca/en/cs/sp/sdc/evaluation/sp-ah053e/page00.shtml   Quasi-Experimental Evaluation  


Statnotes  http://faculty.chass.ncsu.edu/garson/PA765/design.htm   has this brief overview.


Threat to validity   http://psych.athabascau.ca/html/Validity/   overview of threats to validity. See part 1.


Research Design Lessons   http://core.ecu.edu/psyc/wuenschk/DesignLessons.htm   lectures in word.


Research Design Explained   http://www.markwebtest.netfirms.com/teachRDE/start/default.html   class notes.


This Research Methods class   http://www.csulb.edu/~msaintg/ppa696/696menu.htm   has chapters on experimental and quasi experimental design


Johnson's educational research  book   http://www.southalabama.edu/coe/bset/johnson/dr_johnson/2lectures.htm   has chapters (9 and 10) that cover experimental and quasi experimental design. These chapters are fairly detailed.


Resources to design and carry out rigorous evaluations.   http://www.evidencebasedpolicy.org/default.asp?sURL=ombII   various papers such as this "Which Study Designs Can Produce Rigorous Evidence of Program Effectiveness? A Brief Overview"


Identifying and Implementing Educational Practices Supported By Rigorous Evidence: A User Friendly Guide   http://ies.ed.gov/ncee/pubs/evidence_based/evidence_based.asp   "This Guide seeks to provide educational practitioners with user-friendly tools to distinguish practices supported by rigorous evidence from those that are not."


The Core Analytics of Randomized Experiments for Social Research, by Howard S. Bloom    http://www.mdrc.org/publications/437/abstract.html   "This paper ... provides a compact discussion for faculty members, graduate students, and applied researchers of the design and analysis of randomized experiments for measuring the impacts of social or educational interventions."

The Politics of Random Assignment, Implementing Studies and Impacting Policy, by Judith M. Gueron   http://www.mdrc.org/publications/45/workpaper.html   How to get organizations to agree to do random assignment.
 

How Random Must Random Assignment Be in Random Assignment Experiments?   http://www.srdc.org/en_publications.asp?type=8       by Paul Gustafson, "This technical paper reviews options for different approaches to randomization used in experimental studies that measure program impacts"


Gerardo Munck has a methods paper   http://www-rcf.usc.edu/~munck/research/methods.html   See this paper  “Research Designs”., and “Ten Fallacies About Qualitative Research”.


Propensity Score Analysis


Urban institute paper   http://www.urban.org/toolkit/data-methods/propensity.cfm   explanation of what it is and non technical overview of how to do it.


Applications and graphics for propensity score analysis   http://www.albany.edu/~jz7088/documentsSpring04.htm   Lecture 26 notes. A paper by Pruzek and Helmreich. Page 5 and 6 explain the basic idea.

A Comparison of Propensity Score Analysis to Analysis of Covariance: A Case Illustration   http://works.bepress.com/john_fraas/25/   paper by Fraas, explaining PSA, and some how to do it.


Reducing the Impact of Selection Bias with Propensity Scores   http://www.chrp.org/propensity/   some slides from a class, some on what it is, some on how to.


Papers by Rajeev Dehejia   http://www.nber.org/~rdehejia/cvindex.htm   one paper from 2005 is "Practical Propensity Score Matching" and another from 2002 is "Propensity Score Matching Methods for Non-Experimental Causal Studies"


The propensity score and estimation in nonrandom surveys - an overview   http://www.statistics.su.se/modernsurveys/   see publications. This paper is about weighting and websurveys. Also see paper number 24.


The case against null hypothesis significance testing.


The Case Against Null Hypothesis Significance Testing: Flaws, Alternatives, and Action Plans   http://meeting.aomonline.org/2007/index.php?option=com_content&task=view&id=147&Itemid=1   "The purpose of this workshop is to increase the awareness among management researchers of the severe limitations of Null Hypothesis Significance Testing (NHST) and to introduce alternative approaches based on effect size measures and confidence intervals."  At an Academy of Management annual meeting. Presented by William H. Starbuck, Jose M. Cortina and Eric Abrahamson.


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last updated 12/28/08
last verified 12/28/08


These didn't work on 12/28/08.  I'll check again.

Susan Losh's home page   http://mailer.fsu.edu/~slosh//Index.htm    links to her class
Intro statistics and data analysis  http://edf5400-01.fa04.fsu.edu/Overview.html   some basic notes on making tables, univariate, bivariate and regression analysis.

Susan Losh's home page    http://garnet.acns.fsu.edu/~slosh//Index.htm     links to another class:
basic research methods guides  http://edf5481-01.fa02.fsu.edu/Overview.html   for some basic notes on experiments and quasi experiments.

Propensity score analysis: a new method for analysing register data  http://www.escardio.org/congresses/europrevent2006/Pages/resources.aspx   presentation by T. Kurth. A few slides explain what PSA is.