Controls and additive series

Slides:

Advertisements

Similar presentations

McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc.,All Rights Reserved. Part Three SOURCES AND COLLECTION OF DATA.

Advertisements

Randomized Complete Block and Repeated Measures (Each Subject Receives Each Treatment) Designs KNNL – Chapters 21,

Chapter 9 Choosing the Right Research Design Chapter 9.

Randomized Experimental Design

Chapter 4Design & Analysis of Experiments 7E 2009 Montgomery 1 Experiments with Blocking Factors Text Reference, Chapter 4 Blocking and nuisance factors.

DOX 6E Montgomery1 Design of Engineering Experiments Part 3 – The Blocking Principle Text Reference, Chapter 4 Blocking and nuisance factors The randomized.

Jeff Beard Lisa Helma David Parrish Start Presentation.

© 2010 Pearson Prentice Hall. All rights reserved The Complete Randomized Block Design.

CHAPTER 8 EXPERIMENTAL DESIGN.

Controls and additive series. Group exercise: Read your stream control example, and decide on: (1) What is wrong with the design? (2) How you might fix.

Research Methods in MIS: Experimentation Dr. Deepak Khazanchi Acknowledgment: Some of the information in this presentation is Based on Cooper and Schindler.

© 2001 Dr. Laura Snodgrass, Ph.D.1 Basic Experimental Design Common Problems Assigning Participants to Groups Single variable experiments –bivalent –multivalent.

Nasih Jaber Ali Scientific and disciplined inquiry is an orderly process, involving: problem Recognition and identification of a topic to.

1 Introduction to mixed models Ulf Olsson Unit of Applied Statistics and Mathematics.

Some Notes on the Design and Analysis of Experiments.

BHS Methods in Behavioral Sciences I May 19, 2003 Chapter 9 (Ray) Within-Subjects Designs (Cont.), Matched-Subjects Procedures.

Regression Part II One-factor ANOVA Another dummy variable coding scheme Contrasts Multiple comparisons Interactions.

1 Chapter 3: Experimental Design. 2 Effect of Wine Consumption on Heart Disease Death Rate **Each data point represents a different country.

Chapter 14 Cooper and Schindler

Experimentation Chapter 14 Cooper and Schindler. What is Experimentation? Causal method Allow the researcher to alter systematically the variables of.

Experimental Design: One-Way Correlated Samples Design

The Randomized Complete Block Design

Experimental design. Experiments vs. observational studies Manipulative experiments: The only way to prove the causal relationships BUT Spatial and temporal.

1 Experimental Design. 2  Single Factor - One treatment with several levels.  Multiple Factors - More than one treatment with several levels each. 

Blocks and pseudoreplication

EDCI 696 Dr. D. Brown Presented by: Kim Bassa. Targeted Topics Analysis of dependent variables and different types of data Selecting the appropriate statistic.

Ledolter & Hogg: Applied Statistics Section 6.2: Other Inferences in One-Factor Experiments (ANOVA, continued) 1.

Single-Factor Studies KNNL – Chapter 16. Single-Factor Models Independent Variable can be qualitative or quantitative If Quantitative, we typically assume.

Experimental design.

The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 4 Designing Studies 4.2Experiments.

Collection of Data Jim Bohan

Analysis of Experiments

ANOVA Overview of Major Designs. Between or Within Subjects Between-subjects (completely randomized) designs –Subjects are nested within treatment conditions.

 Get out homework and discuss with neighbor.  Be prepared with any questions you might have.  Get out materials for notes.

1 G Lect 13b G Lecture 13b Mixed models Special case: one entry per cell Equal vs. unequal cell n's.

Experiments: Part 2.

Experimental Design and Analysis of Variance

Research Methods: Concepts and Connections First Edition

From: Galerkin Solution of Stochastic Reaction-Diffusion Problems

Experimental Research Designs

Arrangements or patterns for producing data are called designs

Single-Variable, Independent-Groups Designs

Part Three SOURCES AND COLLECTION OF DATA

Journal of Vision. 2016;16(15):21. doi: / Figure Legend:

Research Design & Analysis II: Class 10

2 independent Groups Graziano & Raulin (1997).

BHS Methods in Behavioral Sciences I

Arrangements or patterns for producing data are called designs

Experiments: Part 2.

Evaluating research Is this valid research?.

Matching Methods & Propensity Scores

Latin Square Designs KNNL – Sections

Analysis of Variance (ANOVA)

Single-Variable, Correlated-Groups Designs

The Randomized Complete Block Design

Randomized Complete Block and Repeated Measures (Each Subject Receives Each Treatment) Designs KNNL – Chapters 21,

Correlated-Groups and Single-Subject Designs

Fixed, Random and Mixed effects

Experiments We wish to conduct an experiment to see the effect of alcohol (explanatory variable) on reaction time (response variable).

Experimental design.

Warm Up Compare and contrast the following concepts as they relate to designing studies and experiments: Stratified Random Sample Blocking How are they.

Experimental Design Project

Chapter 11 Principles of Experimental Design.

Principles of Experimental Design

Experimental Design Statistics.

Standard DA-2 Indicator 2

Analysis of Variance (ANOVA)

Principles of Experimental Design

If you have your parent letter, please turn in at my desk (scissors on my desk). Get out your homework and materials for notes!

Three important principles of experimental design are:

Presentation transcript:

Controls and additive series

Rule #1 Make sure your control, is actually a control e.g. non-lethal presence of predators in bromeliads….

Caged Predator Free Predator No Predator

Caged Predator Free Predator No Predator

Additive controls… Group exercise: Read your stream control example, and decide on: (1) What is wrong with the design? (2) How you might fix it.

Scenario 1 Before After A B C A B C

Scenario 2 B C A + pollutant E F D - pollutant

What is the probability that the 3 “worst” streams are randomly assigned to the pollutant treatment?

Scenario 3 + chemical in alkaline solution control Before After B C B D D control

Scenario 4 A B C Before After D E F + pollutant control

Scenario 5 ?

Insect abundance = m1 * width + m2 * dioxin + m3 * width*dioxin + Y-intercept (and error)

Summary of control types Which scenarios lacked: Control for initial conditions? Unmanipulated, contemporaneous control? Control for side effect of manipulation? Control for covariates? Control for non-target response?

BACI design Before After Control Impact Unmanipulated, contemporaneous control Initial conditions Eg. Scenario 3 Before After + pollutant Before After control

BACI design Before After Control Impact Unmanipulated, contemporaneous control Initial conditions Before After control + pollutant

Example of BACI design: on forest fragments and birds Ernest Leupin’s study on forest fragments and birds

Sicamous Creek Research Forest Figure 2. Experimental layout and treatments at the Sicamous Creek Experimental Forest. A- Uncut Reserves, B- 0.1ha openings, C- Selection Cut, D- 10 ha opening, E- 1ha openings . Each Treatment was replicated three times. Dashed line indicates the sampling extension of one uncut reserve.

Figure 3. Aerial view (south-west) of the resulting forest matrix after harvest.

How can we analyze BACI designs? Randomized block? A treatment x date ANOVA? Before After + pollutant control A B C D E F What is n? What is k? How many independent experimental units in total?

How can we analyze BACI designs? Randomized block? A treatment x date ANOVA? Before After + pollutant control What is n? What is k? How many independent experimental units in total? A B C G H I D E F J K L

How can we analyze BACI designs? Two separate ANOVAs / t-tests? Before After + pollutant control Different? Different?

How can we analyze BACI designs? Two separate ANOVAs / t-tests? Impact sites Y variable before after before after before after before after A B C

How can we analyze BACI designs? Need to match the number of datapoints with the number of experimental units Need to take advantage of built-in control for stream identity

How can we analyze BACI designs? One solution: Use difference between before and after as the data! Before After Difference + pollutant A B C A B C A B C Before After Difference control D E F D E F D E F