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Copyright © 1995 Demosthenes Lorandos

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EXPERT WITNESSES: BEYOND JUNK SCIENCE

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AND DAUBERT

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Thursday , April 6, 1995 Troy -- MSU Management Education Center

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Course Handbook

The Institute of Continuing Legal Education 1020 Greene Street Ann Arbor , Michigan 48109 1444 (313) 764-0533 FAX (313) 763 2412

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DEMOSTHENES LORANDOS

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Dr. Lorandos is a licensed clinical psychologist and attorney . Dr . Lorandos has been qualified as an expert in the probate, civil and criminal courts of Michigan well over a hundred times. Dr. Lorandos graduated from the San Francisco State College, earned a masters degree from the New School for Social Research and after four years of study in philosophy of science, earned a doctorate in clinical psychology from Union Graduate School . Dr. Lorandos’ career in psychology spans twenty-five years . He was the president of the Michigan Psychological Services, Inc. , a nationally recognized treatment and research program with offices in Ann Arbor, Flint , Saginaw and Houghton Lake . Dr. Lorandos has taught at Indiana University , Central Michigan University and the National Institute of Health . He is a Fellow and Diplomate of the American Board of Medical Psychotherapy , a Fellow of the American Orthopsychiatric Association as well as a member of the California Psychological Association . Dr . Lorandos retired from active practice of psychology in 1989 to pursue law studies with the University of Detroit where he graduated with honors in 1991. Dr. Lorandos has been admitted to practice in both Michigan and California. He is a member of the American and Michigan Trial Lawyer’s Associations . Dr . Lorandos’ latest publication " Myths and Realities of Sexual Abuse Evaluation and Diagnosis: A Call for Judicial Guidelines " will be published this summer by the international journal Issues in Child Abuse Accusations .

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Finding the Right Expert

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Demosthenes Lorandos Consultants in Behavioral Science & Law

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Brighton , Michigan

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FINDING THE RIGHT EXPERT by: Demosthenes Lorandos Consultants in Behavioral Science and Law Expert Banks

There are many " banks " of experts listed in a variety of attorney publications such as A.B.A. Journal; TRIAL; Michigan Bar Journal; Michigan Lawyer’ s Weekly; M T.L.A Quarterly , et cetera.

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Most, if not all " banks" are staffed by sales people who are knowledgeable about their members and will provide free consultation about their services over the 800 number . Commonly used Expert Witness Banks ( listed alphabetically ):

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American Medical Forensic Specialists, Inc. 1-800-275-8903 - 2,000 selected physicians Expert Finders, Inc . 1-800-274-0353 - Medical , Dental & Hospital negligence

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800 Numbers are often available for the " banks" and should be used

Expert Resources, Inc. 1-800-383-4857 - 21 Offices, Experts in all fields nationwide

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Expert Witness Search Service 1-800-526-5177 - $ 50.- search fee, computerized databank

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Forensic Medical Advisory Service 1-610-825-5559 - Medical, Hospital & Product liability Medical Review Foundation, Inc. 1 800-336-0332 - Offers C.L.E. in Med Mai & Personal Injury

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Medical Witnesses 1-800-431-1777 - 2-3 Wk reports, local attorney references Medically Dedicated , Inc. 1-800-634-3744 - MD’ s, Chiropract. , Dentists, Nurses, etc. Medically Speaking 1-800-633-7754 - Low fees, IME chaperones, Exhibits

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Institute of Continuing Legal Education


National Academy of Expert Witnesses, Inc. 1-800-296-6239 - Attorney to Attorney referrals, one time fee

National Consultant Referrals , Inc. 1-800-221-3104 - No charge search , Experts many fields National Forensic Center - Publishes 1,400 pg Expert Directory & texts

1-800-526-5177

National Medical Services, Inc.

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Toxicology spec , Laboratories, & Experts

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1-800-522-6671

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Medical & Hospital experts, Personal service

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Saponaro, Inc. 1-800-327-3026

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Physicians for Quality 1-800-248-3627 - Flat fee, Low cost, 5,000 Physicians nationally

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Steven Lerner & Associates 1-800-952-7563 - 6,850 Physicians, Nurses, Pharmacists Technical Advisory Service for Attorneys 1-800-523-2319 - 18,500 Experts, every imaginable field

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Technical Assistance Bureau , Inc. 1-800-336-0190 - Medicine, Commerce, Industry , Science

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A.T.L.A. Exchange 1050 31st St., NW Washington, D.C. 20007 1-800-344-3023 Fax 202-337-0977

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Attorney group Expert Witness Banks:

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A.T.L.A. offers a number of services, including:

Expert Database Recovery Comparison Database Document Bank Deposition Bank et cetera

M.T.L.A. 501 South Capitol Avenue - Ste 405 Lansing , Michigan 48933 1-517-482-7740 Fax 517-482-5332 Institute of Continuing Legal Education

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M.T. L.A . offers a number of services, including:

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Expert Database Pleadings & Brief Banks Interrogatory Books Defense Witness Deposition Bank et cetera

Universities

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University faculty are directly available without the "bank " middleperson .

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One draw back, is that without the middle-person, attorneys must " screen " faculty themselves.

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Universities are proud of their faculty and administrators and seek to get them into the public-eye through their Media, or Public Relations offices. Contact for lists and sourcebooks of university experts:

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Media Guide to Experts University of Michigan News & Information Services 412 Maynard Street Ann Arbor , Michigan 48109-1399 313-764-7260

Media Guide to Experts Michigan State University Media - Communications Department 401 Olds Hall East Lansing , Michigan 48824 517-355-2281

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E.M .U . Media Guide Eastern Michigan University Public Information Department 18 Welch Hall Ypsilanti, Michigan 48197 313-487 4400

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C M.U. Sourcebook Central Michigan University Public Relations Office

201 West Hall

N.M .U . Experts Directory Northern Michigan University

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Communications Office 607 Cohodas Building Marquette, Michigan 49855 906-227-2720

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W.M .U . Media Guide Western Michigan University Public Relations - Communications 3010 Administration Building Kalamazoo, Michigan 49008 616-387-2373

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Mt. Pleasant , Michigan 48859 517-774-3197

U of D - Mercy Media Sourcebook

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University of Detroit - Mercy Marketing & Public Affairs Dept. 4001 West McNichols Detroit, Michigan 48219 313-933-1254

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Media Guide Lawrence Technological University Alumni University Relations Dept. 21000 West Ten Mile Road Southfield , Michigan 48075 810-356-0200

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The "independent" experts

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Usually , " independents " are local , court appointed or word-of-mouth selected experts.

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Family and Probate law practitioners often encounter the " regulars " in custody , counseling or child protective proceedings.

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Bias and pre judgement on the part of the Court or the regulars may come about as a natural result of working together and must be monitored.

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Often , "independents " are local heavy hitters who are impressed with their own track record.

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Medical Malpractice and Psychiatry /Psychology prone criminal defense attorneys encounter " regulars" in these arena as well. A willingness to stretch the proofs, or water-down the science into what is referred to as " hyperclaiming " and "causism " must be guarded against. (See: sections V & VI infra )

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A vigorous Voir Dire into the principles and methodology underlying the proffered opinions is the best plan for dealing with regulars.

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Pin your expert down in pre-trial consultation to the specific , scientifically defensible underpinnings to her opinion.

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This other person said she was good.

Determine when this expert " was good "

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Was this expert " good " in the Davis/ Frve era?

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Check with colleagues, M.T L A. etc and your expert, for deposition or video of previous court appearances and attempt to build your direct examination in a manner that you and your expert believe is most effective and honest.

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Determine in pre trial consultation what the secondary gains are for the independent.

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The relaxed standards of the Davis/ Frve era may have allowed a less than knowledgeable "expert " to be qualified and offer un-scientific opinions.

The relaxed standards of the Davis/ Frve era may have allowed a less than well qualified "expert " to pontificate

upon her own experience. 2.

Was this expert " good " in the Daubert " principles & methodology " era?

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Has this expert had her feet held to the fire of a vigorous "principles & methodology " Voir Dire?

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If so, this may really be "good ".

(2)

If not , find out how this expert was qualified in previous outings.

Determine how this expert " was good ". What basic issues were tried in previous outings?

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If so, determine the interface and create a plan for similar testimony.

(2)

If not, find similarities in the style of presentation.

What mode of direct examination was utilized that caused others to find that this expert " was good "?

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Did the expert write out the previous direct examination? (1)

If not, call your colleague back and determine how the winning examination was developed .

How do you know who is really an expert

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Two tiers to the determination of who is & who isn’ t an expert. MRE 702 and Daubert v Merrell Dow Pharmaceuticals Inc .. 509 U S . 113 S Ct 2786, 125 L Ed 2d 469 , (1993).

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If so, determine the best method for duplication with your facts and issues.

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(2)

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Do previous basic issues correspond to yours?

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First Tier - Overt qualifications , selection criteria , statute and Davis/ Frye era case law:

MRE 702 provides:

If the court determines that recognized scientific, technical , or other specialized knowledge will assist the trier of fact to understand the evidence or to determine a fact in issue, a witness qualified as an expert by knowledge, skill , experience, training , or education, may testify thereto in the form of an opinion or otherwise.


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Overt Qualifications include: (1)

Experience Is it on point to trial issues

(2)

Employment history Is there a relevant interface with trial issues

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Licenses

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Are they current or limited in some relevant

(4)

Publications

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If any , do they hurt us or help us

Academic appointments Classes taught, research positions, grants

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Advanced degrees Earned degrees, diplomates, fellow status etc.

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Honors received Academic, Professional or Community related Professional Associations Memberships , Elective office, committees Board Certifications Eligibility requirements, Examinations required

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Autonomy - Ability to speak freely Beholden to Business, Industry , Academia

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Full time practice Nature of practice, locations, persons seen

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% of Income from Expert work How much $ or % income from Ct. work

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Appropriate area of expertise in discipline The degree of " fit " in experts work/ research exp.

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Times qualified in court Which courts, where, when , what subjects

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Recommendation of colleagues Reputation in the field , status

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Selection criteria include:

Fit of credentials to issues in trial Is this ’ second nature’ to this expert

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Experience in public & private sectors ’ Real world’ experience, knowledge of bureaucrats

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Experience Relevance of work history to trial issues

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Cost Cost/Benefit analysis with this expert

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Communication abilities Ability to communicate with counsel & client

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Explanation abilities Capacity to explain difficult ideas

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Cross Examination skills Ability to think on her feet

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Appearance and demeanor Fat/Thin , Tall /Short, Pedantic/ Homespun

Soundness & Reasonableness of Argumentation Forthright, To the point, Economy of words

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Intuitive reasoning abilities Gut level sense of issues & complex ideas

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Availability For trial , Depositions, Pre-trial planning

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Availability of support personnel Research , Laboratory assistants, technicians

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Availability to act as Pre-Trial consultant Cost/ Benefit analysis for Pre-Trial & Issue

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Flexibility Scheduling , Idea patterns, Sense of issues

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Local Appeal Previous exposure , Knowledge of trial locale


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Statute provides practitioners in medical malpractice law , basic qualification criteria: MCLA 600.2169(2), MSA 27A.2169(2), amended by 1993 PA 78 (effective April 1, 1994), provides that when determining the qualifications of an expert witness in a medical malpractice case, the court must evaluate:

(1)

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The educational and professional training of

the expert witness. The area of specialization of the expert witness. The length of time the expert witness has been engaged in the active clinical practice or instruction of the health profession or specialty. The relevancy of the expert witness’ testimony.

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Davis/ Frye era case law provides a rough template for the expert wary trial attorney , to glean qualification criteria. In example:

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Voiceprint or Auditory spectrographic analysis. Cannot be validated as reliable by impartial and disinterested experts. People v Tobev. 401 Mich 141 , 257 NW2d 537 (1977)

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Truth Serums. Sodium pentothal / brevital sodium used as " truth serum " cannot be validated as

reliable by impartial and disinterested experts. People v Cox , 85 Mich App 314, 271 NW2d 216 (1978)

Fingernail analysis. General acceptance and reliability not established. People v Weslev . 103 Mich App 240, 303 NW2d 194 (1981), aff’ d , 412 Mich 375 , 365 NW2d 692 (1984)

Thermography. General acceptance by impartial and disinterested experts as to reliability not established. Kluck v Borland. 162 Mich App 695, 413 NW2d 90 (1987)

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Polygraph. Despite constant revision and scientific research , polygraph operators still cannot demonstrate sufficient reliability for admissibility. People v Ray , 431 Mich 260 , 430 NW2d 626 (1988)

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Hypnosis & Hypnotically refreshed memory. The process of hypnosis is not a reliable means of restoring memory. All post hypnotic testimony is unreliable. People v Lee , 434 Mich 59, 450 NW2d 883 ( 1990 )

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Second Tier - Daubert reliability & validity considerations. It is essential to understand key Daubert concepts to guide you in a determination of whether this person is really an expert.

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Blood grouping by electrophoresis General acceptance by impartial and disinterested experts as to reliability not established . People v Young, (after remand ) 425 Mich 470, 391 NW2d 270 (1986) & People v Gistover. 198 Mich App 44 , 472 NW2d 27 (1991 )

KEY DAUBERT CONCEPTS

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TRIAL COURT

Is the gatekeeper who must make a preliminary assessment as to whether the reasoning and methodology proffered are

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scientifically valid. 113 S Ct at 2796, 125 L Ed 2d at 482.

TRIAL COURT Must ensure that proffered testimony is relevant and reliable with a focus solely on principles and methodology. 113 S Ct at 2797, 125 L Ed 2d at 484. EVIDENTIARY ADMISSIBILITY Shall be based upon reliability determined by the degree of scientific validity. 113 S Ct at 2795, 125 L Ed 2d at 481.

SCIENTIFIC METHODOLOGY

Means generating hypotheses and testing them to see if they can be falsified. Has the technique been " tested " is the key question. 113 S Ct at 2796, 125 L Ed 2d at 483.


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SCIENTIFIC KNOWLEDGE Is that which is derived from the empiricism of the scientific method. 113 S Ct at 2795, 125 L Ed 2d at 482. EXPERTS Must be grounded in the methods and procedures of science. 113 S Ct at 2795, 125 L Ed 2d at 481.

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EXPERTS Must understand the error rate involved in their scientific techniques. 113 S Ct at 2797, 125 L Ed 2d at 483.

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EXPERTS Must know and base their opinions reliably on the datum of their discipline. 113 S Ct at 2796, 125 L Ed 2d at 482.

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Reasoning - Empiricism - Methodology - Hypothesis Testing Error Rates - Validity - Reliability - Scientific Knowledge - Datum of a Discipline These are admissibility criteria we must know and understand.

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Reasoning in science has essential characteristics , Induction, Deduction and the Inferences built with them. (1)

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If the proposed expert does not understand or cannot explain these important concepts and their relationship to the issues at bar, she is not an expert by Daubert.

Induction Scientists don’ t begin by trying to prove something , they begin by trying to explain something . Collecting many observations and reasoning out a general conclusion - from the particular to the general - is called induction. (2)

Deduction

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With general statements and theories, derived from induction, scientists attempt to deduce explanations and predictions reasoning from the general to the particular - is called deduction.

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(3)

Inference The process of reasoning whereby the scientist deduces one proposition logically

from another. Empiricism in science grows out of the philosophical traditions of John Locke ( 1632-1704), George Berkeley ( 1685-1753) and David Hume (1711-1776). Knowledge is that which can be perceived , (a la "I’ m from Missouri.... ya gotta show me"). Two specific kinds of empiricism are of importance to scientists and attorneys today: Logical Empiricism & New Philosophy of Science. Logical Empiricism This is the dominant kind of empiricism in the mid-twentieth century. The predominant proponents are Carl Hempel and Karl Popper. The Daubert Court speaks directly to this (out dated) philosophy of science.

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Basically , " testability " of a theory and its "falsifiability " are the distinguishing features of scientific knowledge.

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New Philosophy of Science - Empiricism This represents the cutting edge of the philosophy of science today . Some of the chief proponents are Thomas Kuhn , Harold Brown and Paul Feyerabend. This work requires scientists and legal scholars to continually refine ideas of causation. Basically , " presuppositions " and basic ways of perceiving permeate every fabric of hypothesis and theory construction. Science mixes imagination and method . It is ever changing. New data change assumptions and revise well established " facts".

Methodology requires that the researcher must: (a) Clearly formulate the research idea in words; (b ) Describe the issue/ problem to be studied in such a way that useful empirical data (preferable reducible to numbers) can be collected; and

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(c) Focus upon things or events which are

accessible and observable by others. There are two main avenues: Observational and Experimental.

Observational modes of science:

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anthropologists, primate biologists. Correlational studies - astrophysicists , paleontologists. Surveys - economists, epidemiologist , sociologists. Co-hort studies - psychologists , epidemiologist.

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Field studies

Experimental modes of science: Researchers, develop a workable hypothesis, with special attention to value-laden selection issues. Next, initial conditions are set up with attention to dependant , independent and intervening variables. Next, the experiment is carried out with double-blind conditions, variable control and other standardization procedures. Results are observed , data gathered , analyzed , interpreted and reported with special attention given to mathematical

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determinations of conclusion contents and generalizations. [See: A Brief Glossary and Bibliography]

Hypothesis testing , involves the processes of induction, inference and deduction as well as the procedures and methodology described above. In addition , four different activities are involved: (1)

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Internal consistency This is particularly difficult in mathematically based hypothesis construction. Hypotheses cannot be selfcontradictory or logically improper.

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(3)

Consistency with previous hypotheses For a new hypothesis to replace an old one (as in General Relativity theory replacing Newtonian theories), it must overlap in a consistent manner.

(4)

Empirical evidence validity The evidential underpinnings for moving from one hypothesis concerning a phenomena to another is the empirically verified power of the new hypothesis to explain the phenomena more cogently.

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Logical structure Hypotheses must make observable phenomena intelligible. A valid hypothesis will have the power to describe conditions, mechanisms and processes in the phenomena it’s offered to explain.

Error rates, in scientific expert testimony are crucial to the conclusions which may be drawn by the trier of fact. For example, if the witness testifies that the defendant drove away in a blue car and it is established that the defendant has a blue car without a determination of how many blue cars populate the area, we have a base rate error. There are five broad categories of error:


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Theoretical error Measurements of data are constructed with a theory of measurement thought to be appropriate to the phenomena being assessed. If the phenomena turn out to be too complicated for the original measurement tools, theoretical error occurs.

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Static errors Measuring instruments work in some environments and not in others. Instrumentation gain errors , technician reading errors, processing errors, resolution errors are static errors as well.

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Dynamic errors When measurement processes must change or move or develop while the process of

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measurement is ongoing , dynamic errors

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Measurement insertion errors When the process or measurement alters what is being measured.

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Data analysis measurement errors Statistical and computational errors , as well as subject selection , variable selection and data-dropping errors are sometimes found in the service of " hyperclaiming " and "causism ". For example, the "cold fusion " results reported in Utah were quickly published but could not be replicated .

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Validity , in science has been taken by the Daubert Court to be the touchstone of evidentiary admissibility. There are many kinds of validity Several important types are:

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Internal validity The process of validation by which we infer that a relationship between two variables is causal.

(2)

Construct validity The extent to which a test or experiment is

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measuring what we think it is measuring ( the construct ).

External validity

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The ability to generalize to particular persons, settings or things from the data. (4)

Statistical conclusion validity Proper statistical methods lead to testing the significance of a relationship between factor A and factor B. Null hypotheses and Type I and Type II errors and statistical conclusion validity lead to statements about causation.

Reliability , in scientific methods and conclusions deals with replicability and consensus. In the main, reliability is of two types:

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Inter rater reliability This type of reliability asks if the test or measurement is utilized in the same manner with the same subjects and a different experimenter, will the results be the same.

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Test re test reliability This type of reliability requires the same results when the procedure or technique is done over and over again in the same

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Scientific knowledge, is distinct from legal knowledge or the "facts" of the " trier of fact ". Hypothesis testing in science is not a passor-fail proposition.

(2)

The truth of a scientific hypothesis can never be established conclusively, only contingently. The history of science testifies to this reality.

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Datum of a discipline is the sine qua non of an expert. She must be familiar with the basic compendium of knowledge which is the history , methods, procedures, description of ethical principles and accumulated scientific knowledge of her discipline. An explanatory analogy (1)


A model or explanation or technique is accepted in science only when scientific procedures have been utilized to determine if the predictions made by the model/ explanation/ technique, are accurate and a sufficient consensus of scientists have determined that the methods or testing or analysis were adequate.

Attorneys must pass the Multi State Bar Examination, a 200 item, multiple choice test encompassing: Torts, Contracts, Criminal , Evidence, Property , and Constitutional law .

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The "Multi State " is designed to test proficiency in these basic areas of legal thinking and practice.

(3)

The candidate-lawyer , must pass this examination with a score (in most states) at or above the national mean.

(4)

Very much the same scenario exists for experts in almost every field. In our pre¬ trial planning and Voir Dire , we must assess Daubert’ s foundational issue for the proffered expert - her knowledge of the datum of her discipline.

Avoiding embarrassing cross examination

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The litigator must familiarize herself with and use the qualification and selection criteria described above to greatest advantage.

The litigator must ascertain if the court is stuck in the out moded Davis/ Frye criteria and develop a plan of action.

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If the trial court remains stuck in the Davis/ Frye criteria , the litigator must utilize an offer of proof , an evidentiary hearing , a motion in liminie, or some other procedural mechanism to bring the issues of methodology , reasoning , error rates, validity and reliability to the court’ s attention.

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Preparation is as important in litigation as it is in science.

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If these procedural mechanisms are of no avail , the litigator must develop the same awareness in the trial court through Voir Dire .

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(2)

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The litigator must develop an understanding of the foundational issues in Davis/ Frye case law . In example:

Testimony by experts whose livelihood depends on the technique in question will not suffice to show general acceptance under Davis / Frye . Miller v State Farm Mutual Automobile Insurance Co.. 168 Mich App 238, 424 NW2d 31 ( 1988).

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Institute of Continuing Leml ^Auc''*’''

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Expert witnesses in the behavioral sciences must demonstrate objectivity and reliability of proffered scientific testimony. People v Becklev. 434 Mich 691, 456 NW2d 391 (1990)

Utilize colleagues, and attorney groups such as A.T.L.A. and M.T.L.A. liberally in this regard.

b.

Familiarize ones self with MRE 608 and collateral impeachment; MRE 703 and MRE 705 and opinion grounding. Get ready for skeletons in the closet and a history of bias.

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The litigator must attempt to familiarize herself with the orientation , track record , style and previous testimony of the expert.

The litigator must attempt to develop an understanding of the principles and methodology of science.

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Read Daubert v Merrell Dow Pharmaceuticals Inc.. , 113 S Ct 2786, 125 L Ed 2d 469 , (1993). 509 U S

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Review:

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DeLuca v Merrell Dow Pharmaceuticals Inc .. 911 F. 2d 941 (3rd Cir. 1990) on remand 791 F. Supp. 1042 (D. N.J. 1992), aff’ d without op 6 F. 3d 778 (3d Cir. 1993), cert , denied , 114 S. Ct. 691 (1994)

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Christophersen v Allied-Signal Corp. , 939 F. 2d 1106, (5th Cir. 1991) (en banc), cert , denied , 112 S. Ct. 1280 (1992)

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Pick gt least two of the references cited in the Bibliography and read them with a note pad handy.

The litigator must understand " Hyperclaiming *

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Hyperclaiming describes a tendency by expert witnesses to overstate the implications of specific research.

b.

Hyperclaiming is best debunked by an explication of the research design and the statistical methodology utilized.

" Legal Education

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The litigator must understand " Causism *

Causism describes a tendency to imply a relationship between factor A and factor B where the research does not support this conclusion.

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Causism is often given away by the extent to which the expert is committed in a self -serving manner to the "causal relationships " she describes.

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The presence of language such as: " the consequence of" , "as a result " , " the effect of where language such as: " is related to" or " may be inferred from " would have been more appropriate, is usually found with causism prone expert witnesses.

Causism reflects poor scientific training and unethical misrepresentation.

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Hyperclaiming reflects poor scientific training and or an active desire to misrepresent.

Finally , the litigator must remember:

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Improperly tested hypotheses, small or unrepresentative samples, the absence of a comparison group, data dropping and failure to achieve statistical significance are hallmarks of hyperclaiming .

is a first-rate piece of furniture for a man's upper chamber, if he has common sense on the ground floor. "

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" ,Science

Oliver Wendell Holmes, Sr. (1809 - 1894) The Poet at the Breakfast-Table [1872], ch. 5

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A Brief Glossary

A set of statistical procedures developed to compare two or more groups of data.

Coefficient of correlation

Statistical procedure for describing the relationship of two sets of data. Most common is the Pearson r product moment correlation coefficient. Positive correlation: When A happens , B happens Negative correlation: When A happens , B does not

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Analysis of variance ( ANOVA )

happen.

A measure of statistical significance. The 5 % confidence interval means that the resultant mean score will happen only five times out of a hundred .

Control group

A matched group experimental or observational subjects who did not get the treatment/ technique.

Deduction

Reasoning from the general to the particular. With general statements and theories, derived from induction, scientists attempt to deduce explanations and predictions.

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Confidence interval

In an experiment where a control group and an experimental group are compared , the dependant variable is the variable that the experimenter measures. The variable who’s value "depends " on the effect of the independent variable.

Error rate

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Empiricism

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Dependant variable

Knowledge is that which can be perceived. Logical empiricism - The " testability " of a theory and its"falsifiability " are the distinguishing features of scientific knowledge. Empiricism New Philosophy of Science Science mixes imagination and method. New data change assumptions and "facts". " Presuppositions " infuse hypothesis and theory construction.

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The % of occurrence of errors usually resultant of improper generalizations from data. Type I error: a null hypothesis is rejected when it should be retained. Type II error, a null hypothesis is retained when it should be rejected.

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A controlled method of hypothesis testing where the experimenter attempts to control all intervening variables and in a standardized way, test the impact of the independent variable upon the subjects of the experiment.

Factor analysis

A technique of data reduction used to create a set of linear combinations of variables.

Hypothesis

A proposed explanation or description of the world . Consistency with itself, with previous hypotheses, logical structure and the ability of the hypothesis to be empirically verified describe its power to explain and describe.

Incidence

The number of new occurrences or cases occurring over a specified period of time.

Independent variable

In an experiment where a control group and an experimental group are compared , the independent variable is the variable that the experimenter manipulates. The variable of interest.

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Experiment

Collecting many observations and reasoning out a general conclusion from the particular to the general.

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Measures of central tendency

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Induction

Multivariate analysis

Descriptions of the central value in a distribution around which other values are distributed . Mean - The arithmetic average. Median - The middle value in a set of rank ordered values. Mode - The value that appears most frequently in a set of measurements.

Methods for describing the relationship of three or more variables. Canonical correlation - a technique for

simultaneously determining the relationship of combinations of two or more predictions with two or more outcomes. a technique for finding the Discriminant analysis outcome and a linear single a between relationship combination of two or more predictors.

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Multiple regression - a technique where a scaled variable is correlated with a linear combination of independent variables.

A set of statistical methods that do not require restrictive assumptions about population distributions.

Null hypothesis

The testable assumption that there is no significant difference between two random samples. When a null hypothesis is rejected , observed differences are thought to be not caused by chance.

Power

The probability of correctly rejecting the null hypothesis. Power identifies true differences. It is a function of s study’ s sample size, the size of the effect detected and significance criteria.

Predictive value

The ability of a technique or test or explanation , to predict a condition. Positive predictive value - the n of true positives divided by the sum of the n of true positives and false positives. - The probability that a patient with a positive test result does in fact have the condition. Negative predictive value - the n of true negatives divided by the sum of the n of true negatives and false negatives. - The probability that a patient with a negative test result is in fact free of the condition.

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Prevalence

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Nonparametric statistics

The number of cases of a condition that exist. A single measure of Cross-sectional prevalence prevalence at a particular point in time. Lifetime prevalence - A measure at a point in time of the number of persons who had a condition. Point prevalence - The number of persons who have a condition at a particular point in time. Treatment prevalence - The number of persons

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being treated for a specific condition in a specific geographical area at a specific point in time.

Probability

The quantitative statement of the likelihood that a particular event or condition will occur.

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Regression analysis

A method designed to utilize observed data to predict the value of one variable (factor A) in relation to the value of another variable (factor B).

Reliability

Replicability and consensus. Inter-rater reliability - if the test or measurement is utilized in the same manner with the same subjects and a different experimenter, will the results be the same. Test re-test reliability - will the same results occur when the procedure or technique is done over and over again in the same conditions.

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A graph or visual presentation of the relationship between two variables. Linear - positive relationship Curvilinear - negative relationship Nonlinear - no relationship.

Sensitivity

The number of true positives divided by the sum of the n of true positives and false positives. The proportion of occurrences in a population the test or technique is able to accurately predict.

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Scatter diagram

A statistical method for describing distributions of scores. It is derived by squaring each deviation from the mean , taking the average of these squares , and then obtaining the square root of the result.

Validity

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Standard error

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Standard deviation


A measure of how much variation in test results is due to chance and error and how much is due to the effect hypothesized .

The process by which we attempt to accurately communicate and comprehend or control. Construct validity - we believe we’ re measuring what we think it is measuring ( the construct ). Criterion validity - comparing a new test’ s results to another who’ s validity has been established. External validity - generalizability to particular persons, settings or things from the data. Face validity - the measure makes sense to the investigator using it.

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Internal validity - we infer that a relationship between two variables is causal. Statistical conclusion validity proper statistical methods.

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