# Multivariate Analysis of Parametric Data Essay

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Maddox's research design involved a qualitative analysis of consumer behavior in regard to their usage of Web sites for the purpose of gathering prescription drug information as well as product requests. The research design involved the use of a questionnaire to measure the research questions. The questionnaire was placed online on a website belonging to one of the major pharmaceutical firms for a 2-week period., the responses were rated on a five-point (Likert) scale that ranged from 1 for very unimportant or unlikely to 5 for very important or likely.

Do you agree with the following statement?

Maddox (1999) should have used a Repeated Measure ANOVA to test for differences (based on AGE and GENDER) in the set of responses.

No.It would have been better to use the full ANOVA and ANCOVA since its interpretation is easier. The best alternative however s non-parametric ANCOVA and adjusting for differences in age and sex (Koch & Tangen,1999).

Do you agree with the following statement?

Maddox (1999) should have used a Multiple Factor MANOVA to test for differences (based on AGE and GENDER) in the set of responses.

No. This is because Multiple Factor MANOVA is only applicable in cases where there is more than a single dependent variable.In Maddox (1999) case there is only one dependent variable.

5.1c. Do you agree with the following statement?

Get full access

for only $8.97. To show that the effect of AGE and GENDER on each of the dependent variables holding constant the effects of co-variates, Maddox (1999) should have used a Repeated Measure ANCOVA.

Yes.This is because it has a similarity with non-parametric ANCOVA and adjusting for differences in age and sex (Koch & Tangen,1999).

5.1d. Do you agree with the following statement?

To show that the effect of AGE and GENDER on each of the dependent variables holding constant the effects of co-variates, Maddox (1999) should have used a Multiple Factor ANCOVA (that is, Maddos (1999) should have used a MANCOVA).## Essay on

Yes.This is because MANOVA is used basically in evaluating whether a given population means on a given set of dependent variables may vary across the various levels of a factor or even factors (evaluation across all groups)

5.1e. Do you agree with the following statement?

Maddox (1999) should have examined the responses to each of her questions using Multiple Regression, using 0 and 1 for Gender and 1, 2, 3, and 4 for AGE, and should have computed partial correlations thereby holding the effects of one of the predictor variables constant while she examined the effect of the other predictor variable.

Yes.This should have had an almost a similar effects as a Multiple Factor ANCOVA (MANCOVA).

CASE5.2 - MANOVA (Multivariate Analysis of Variance)

Bello, Daniel & Williamson, Nicholas (1985, Fall). The American Export Trading Company: Designing a New International Marketing Institution. Journal of Marketing, 49(4). 60-69.

Daniel Bello & Nicholas Williamson (1985) use MANOVA and ANOVA to test four hypotheses.

In hypothesis 1, Bello & Williamson (1985) state that:

The importance of services provided by export intermediaries is influenced by the type of product exported, export role of the intermediary, and supplier's export sales volume.

In hypothesis 2, Bello & Williamson (1985) state that:

Type of product influences the importance of services provided by export intermediaries in the following manner:

Transaction creating services are more important for differentiating products

Physical fulfilling services are more important for undifferentiated products.

Please do the following tasks:

5.2 Describe the research design.

The research design involve the formulation of hypothesis and then testing them against a national sample of American EMCs.

5.2a. There are so many variables described in this article that it would be helpful to me, if you would tell me who (or what) are the cases.* Then, using the format for a codebook, list the variables (add as many rows as you need to add to the following table), and list value labels for each of those variables.

• Case is a term that was coined by the writer's of BMP, a computer program that was the precursor to BMPD, SAS. SPSS, etc. It was chosen by those writers because BMP was originally written for BioMed research where, in the medical sense, a Cases are individuals. Today, at least in business lingo, a case can be an individual, a division of a company, a company, an industry, a state, a region, a country, or whatever the researcher deems appropriate.

Variables Value Labels

1. Product (p)

2. Export role (r)

3. Supplier volume (v)

5.2b1. Choose either 5.2b1 or 5.2b2.

5.2b1a. Based on Hypothesis 1, write out a multiple regression equation using as your dependent variable importance of services provided and as your independent variables each of the factors influencing the importance of those services.

S= 0.01p+0.07r+0.7v

5.2b1b. Using the terminology of partial correlation/regression, explain how you could show the effect of each of the independent factors, holding constant the effect of the other factors.

By carrying out Dummy-Variable Regression analysis in turns on the various variables.

5.2b1c. Explain why a partial correlation between each these factors and theimportance of services provided if you chose Hypothesis 1 or the (holding constant the other factors) is a better measure of the relationship than simple correlations between each factor and the importance of services provided.

This is because the exact relationship between the variables in not known.This means that no definite equation can be drawn since the dependent variables and the independent ones are not easy to isolate and identify.

Case5.3 - Multiple Regressions

Hise, Richard T; Gable, Myron; Kelly, J. Patrick; and McDonald, James B (1983, Summer). Factors Affecting the Performance of Individual Chain Store Units: An Empirical Analysis. Journal of Retailing, 59(2). 22-39.

Hise, Gable, Kelly,,and McDonald (1983) tried to predict Retail Store Performance based on 18 Variables.

Hise, Gable, Kelly,,and McDonald (1983) measured Performance in terms of Sales Volume

Contribution Income, and Return on Assets

For each of these measures of performance, Hise, Gable, Kelly,,and McDonald (1983) ran StepWise regressions.

5.3. What is the research design?

Questionnaires were used to collect the relevant data for the dependent and independent variables.

5.3a. What is a stepwise regression?

Stepwise regression is noted by Ing and Lai (2011) to be a semi-automated process of building a statistical model by successive addition or removal of variables on the sole basis of the t-statistics of their estimated coefficients.

5.3b. As is shown in Table 2 in Hise, Gable, Kelly,,and McDonald (1983), explain why a predictor (for example, Hours Worked Per Week, in this case), which, on its own, is not a significant predictor (for example of Sales Volume, in this case), remains as a step in the Multiple Regression.

Because such a predictor forms parts and parcel of the correlation matrix that is used in defining the final equation or function.

5.3c. What is multi-colinearity?

This is a case of multiple regression in which the identified predictor variables are themselves very highly correlated.

5.3d. Why is it important to estimate muli-colinearity among independent variables in a Multiple Regression?

In order to find out the nature of relationship that might exists between the independent variables themselves.

CASE5.4 - Multiple Regression

Tharenou, Phyllis (2001, December). The relationship of training motivation to participation in training and development, Journal of Occupational and Organizational Psychology. 74 (5). 599-622.

5.4. What is the research design?

Survey data was collected at Time 1 and Time 2 and then multiple regression analysis used to analyze it.

5.4a. Why did the author choose multiple regression analysis to show the relationship between a set of independent variables and a single dependent variable?

Because of the high number of variables and the complex interaction that might exist between the variables themselves.

5.4b. Given the multiple regression analysis the author conducted, how can we interpret the significance of the various coefficients the author shows to be significant… [END OF PREVIEW] . . . READ MORE

Do you agree with the following statement?

Maddox (1999) should have used a Repeated Measure ANOVA to test for differences (based on AGE and GENDER) in the set of responses.

No.It would have been better to use the full ANOVA and ANCOVA since its interpretation is easier. The best alternative however s non-parametric ANCOVA and adjusting for differences in age and sex (Koch & Tangen,1999).

Do you agree with the following statement?

Maddox (1999) should have used a Multiple Factor MANOVA to test for differences (based on AGE and GENDER) in the set of responses.

No. This is because Multiple Factor MANOVA is only applicable in cases where there is more than a single dependent variable.In Maddox (1999) case there is only one dependent variable.

5.1c. Do you agree with the following statement?

Get full access

for only $8.97. To show that the effect of AGE and GENDER on each of the dependent variables holding constant the effects of co-variates, Maddox (1999) should have used a Repeated Measure ANCOVA.

Yes.This is because it has a similarity with non-parametric ANCOVA and adjusting for differences in age and sex (Koch & Tangen,1999).

5.1d. Do you agree with the following statement?

To show that the effect of AGE and GENDER on each of the dependent variables holding constant the effects of co-variates, Maddox (1999) should have used a Multiple Factor ANCOVA (that is, Maddos (1999) should have used a MANCOVA).

## Essay on *Multivariate Analysis of Parametric Data* Assignment

Yes.This is because MANOVA is used basically in evaluating whether a given population means on a given set of dependent variables may vary across the various levels of a factor or even factors (evaluation across all groups)5.1e. Do you agree with the following statement?

Maddox (1999) should have examined the responses to each of her questions using Multiple Regression, using 0 and 1 for Gender and 1, 2, 3, and 4 for AGE, and should have computed partial correlations thereby holding the effects of one of the predictor variables constant while she examined the effect of the other predictor variable.

Yes.This should have had an almost a similar effects as a Multiple Factor ANCOVA (MANCOVA).

CASE5.2 - MANOVA (Multivariate Analysis of Variance)

Bello, Daniel & Williamson, Nicholas (1985, Fall). The American Export Trading Company: Designing a New International Marketing Institution. Journal of Marketing, 49(4). 60-69.

Daniel Bello & Nicholas Williamson (1985) use MANOVA and ANOVA to test four hypotheses.

In hypothesis 1, Bello & Williamson (1985) state that:

The importance of services provided by export intermediaries is influenced by the type of product exported, export role of the intermediary, and supplier's export sales volume.

In hypothesis 2, Bello & Williamson (1985) state that:

Type of product influences the importance of services provided by export intermediaries in the following manner:

Transaction creating services are more important for differentiating products

Physical fulfilling services are more important for undifferentiated products.

Please do the following tasks:

5.2 Describe the research design.

The research design involve the formulation of hypothesis and then testing them against a national sample of American EMCs.

5.2a. There are so many variables described in this article that it would be helpful to me, if you would tell me who (or what) are the cases.* Then, using the format for a codebook, list the variables (add as many rows as you need to add to the following table), and list value labels for each of those variables.

• Case is a term that was coined by the writer's of BMP, a computer program that was the precursor to BMPD, SAS. SPSS, etc. It was chosen by those writers because BMP was originally written for BioMed research where, in the medical sense, a Cases are individuals. Today, at least in business lingo, a case can be an individual, a division of a company, a company, an industry, a state, a region, a country, or whatever the researcher deems appropriate.

Variables Value Labels

1. Product (p)

2. Export role (r)

3. Supplier volume (v)

5.2b1. Choose either 5.2b1 or 5.2b2.

5.2b1a. Based on Hypothesis 1, write out a multiple regression equation using as your dependent variable importance of services provided and as your independent variables each of the factors influencing the importance of those services.

S= 0.01p+0.07r+0.7v

5.2b1b. Using the terminology of partial correlation/regression, explain how you could show the effect of each of the independent factors, holding constant the effect of the other factors.

By carrying out Dummy-Variable Regression analysis in turns on the various variables.

5.2b1c. Explain why a partial correlation between each these factors and theimportance of services provided if you chose Hypothesis 1 or the (holding constant the other factors) is a better measure of the relationship than simple correlations between each factor and the importance of services provided.

This is because the exact relationship between the variables in not known.This means that no definite equation can be drawn since the dependent variables and the independent ones are not easy to isolate and identify.

Case5.3 - Multiple Regressions

Hise, Richard T; Gable, Myron; Kelly, J. Patrick; and McDonald, James B (1983, Summer). Factors Affecting the Performance of Individual Chain Store Units: An Empirical Analysis. Journal of Retailing, 59(2). 22-39.

Hise, Gable, Kelly,,and McDonald (1983) tried to predict Retail Store Performance based on 18 Variables.

Hise, Gable, Kelly,,and McDonald (1983) measured Performance in terms of Sales Volume

Contribution Income, and Return on Assets

For each of these measures of performance, Hise, Gable, Kelly,,and McDonald (1983) ran StepWise regressions.

5.3. What is the research design?

Questionnaires were used to collect the relevant data for the dependent and independent variables.

5.3a. What is a stepwise regression?

Stepwise regression is noted by Ing and Lai (2011) to be a semi-automated process of building a statistical model by successive addition or removal of variables on the sole basis of the t-statistics of their estimated coefficients.

5.3b. As is shown in Table 2 in Hise, Gable, Kelly,,and McDonald (1983), explain why a predictor (for example, Hours Worked Per Week, in this case), which, on its own, is not a significant predictor (for example of Sales Volume, in this case), remains as a step in the Multiple Regression.

Because such a predictor forms parts and parcel of the correlation matrix that is used in defining the final equation or function.

5.3c. What is multi-colinearity?

This is a case of multiple regression in which the identified predictor variables are themselves very highly correlated.

5.3d. Why is it important to estimate muli-colinearity among independent variables in a Multiple Regression?

In order to find out the nature of relationship that might exists between the independent variables themselves.

CASE5.4 - Multiple Regression

Tharenou, Phyllis (2001, December). The relationship of training motivation to participation in training and development, Journal of Occupational and Organizational Psychology. 74 (5). 599-622.

5.4. What is the research design?

Survey data was collected at Time 1 and Time 2 and then multiple regression analysis used to analyze it.

5.4a. Why did the author choose multiple regression analysis to show the relationship between a set of independent variables and a single dependent variable?

Because of the high number of variables and the complex interaction that might exist between the variables themselves.

5.4b. Given the multiple regression analysis the author conducted, how can we interpret the significance of the various coefficients the author shows to be significant… [END OF PREVIEW] . . . READ MORE

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