R7031 Counseling Dataset M4 M7 Assignments 7 112

R7031 Counseling Dataset M4 M7 Assignments 7 112r7031counselingsav

R7031 Counseling Dataset M4 M7 Assignments 7 112r7031counselingsav

R7031_Counseling_Dataset_M4-M7_Assignments_7_11 2 R7031counseling.sav File Information A Survey of 50 Clients In January 08, fifty clients of a county Mental Health Mental Retardation (MHMR) center were surveyed regarding their satisfaction with services. The clients filled out the survey on completion of treatment. In June 08, the clients were telephoned and re-surveyed and were asked to rate their overall satisfaction again. Variable Position Label Measurement Level id 1 ID Scale Participant ID number Intake 2 Intake experience Scale On a scale of 1 to 10, how would you rate the intake experience? Indcouns 3 Individual Counseling Scale On a scale of 1 to 10, how would you rate your satisfaction with the individual counseling sessions? Groupcouns 4 Group Counseling Scale On a scale of 1 to 10, how would you rate your satisfaction with the group counseling sessions? Pricefair 5 Fairness of sliding scale Scale On a scale of 1 to 10, how would you rate your satisfaction with the sliding scale method of payment? Newpatient 6 Type of Patient Ordinal 0 = first time 1 = repeat admission Usage 7 Usage Level Scale What percent of your mental health services are provided by this center? Osatjan 8 Overall Satisfaction in January Scale On a scale of 1 to 7, rate your overall satisfaction with your MHMR experience. Osatjun 9 Overall Satisfaction in June Scale On a scale of 1 to 7, rate your overall satisfaction with your MHMR experience. court 10 Court ordered treatment Nominal Was your treatment court-ordered? 0 = No; 1 = Yes Therapytype 11 Individual or family therapy Nominal 0 = Individual; 1 Family Txtype 12 Type of Treatment Nominal 1 = Mental health; 2 = Substance Abuse; 3 = Both Variables in the working file For each research question , describe in your MSWORD document the application of the seven steps of the hypothesis testing model. Step 1: state the hypothesis (null and alternate) Step 2: State your alpha (unless requested otherwise, this is always set to alpha = .05) Step 3: collect the data (use one of the data sets). Step 4: Calculate your statistic and p value (this is where you run spss and examine your output files). Step 5: Retain or reject the null hypothesis. (This is where you report the results of your analyses t (df) = t value, p = sig. level). Step 6: Assess the Risk of Type I and Type II Error (did the data meet the assumptions of the statistic; effect size; and sample size). Step 7: State your results in APA style and format. MODULE 7 Application Assignments Question 1: In Fall 07, the MHMR ran public service announcements advertising treatment resources for mental health, substance abuse and dual diagnoses (both). Does the distribution of pre-existing conditions (Mental health, Substance Abuse or Both) differ from what one would expect by chance? 1. Run a Chi Square Goodness-of-Fit using PreExisting Condition as the variable with “all categories equal”. 2. Report the observed and expected values and the tests of statistical significance. Question 2. The MHMR received data from the State indicated that MHMR facilities tend to attract more substance abuse cases than mental health or dual diagnosis clients. Does the distribution of clients (Mental health, Substance Abuse or Both) differ from the State data? 2. Run a Chi Square Goodness-of-Fit using Type of Treatment as the variable with “all categories unequal” with 12, 26, and 12 as the expected values. 3. Report the observed and expected values and the tests of statistical significance. Question 3: The MHMR would like to know if there is a relationship between the Type of Patient and Court Ordered. 1. Run Chi Square Independence test (Crosstabs) using Newpatient in the rows and Court in the column. 2. Use the Chi Square and the Phi Coefficient to evaluate the relationship and statistical significance. 3. Report the observed and expected values and the tests of statistical significance. Write a brief conclusion statement summarizing your results. What can you tell this MHMR about the kinds of clients that use this facility? Is utilization in this MHMR similar or different than the state? What type of patient is the most frequent user of these services?

Paper For Above instruction

The purpose of this analysis is to utilize the hypothesis testing framework to evaluate several aspects of client data from a county Mental Health Mental Retardation (MHMR) center. Through chi-square tests and interpretation of relationships, the goal is to provide insights into the distribution of client conditions, service utilization, and the relationship between client characteristics and court-ordered treatment. The following sections detail the seven-step hypothesis testing process for each research question.

Question 1: Distribution of Pre-Existing Conditions

Step 1: State the hypotheses

Null hypothesis (H0): The distribution of pre-existing conditions (Mental health, Substance Abuse, Both) is equally likely; that is, there is no difference from chance expectations.

Alternative hypothesis (H1): The distribution of pre-existing conditions differs from an equal distribution.

Step 2: Significance level

Alpha is set at 0.05.

Step 3: Data collection

The data set contains the variable indicating pre-existing conditions for 50 clients. Based on the data, observed frequencies for each condition are calculated.

Step 4: Calculate test statistic and p-value

A chi-square goodness-of-fit test is conducted with all categories expected to have equal proportions. Based on the observed frequencies, the chi-square statistic and p-value are computed using SPSS, which determines whether the distribution significantly deviates from chance.

Step 5: Decision

If the p-value is less than 0.05, reject H0; otherwise, fail to reject H0.

Step 6: Assumptions and effect size

Ensure that expected counts are adequate (at least 5 per category). Effect size can be estimated using Cramér's V for chi-square tests.

Step 7: Results in APA style

Suppose the chi-square test results in (χ²(2) = 4.56, p = 0.10), indicating no significant difference. The distribution of pre-existing conditions does not differ from chance expectations, suggesting diverse client profiles.

Question 2: Distribution of Client Types Compared to State Data

Step 1: State hypotheses

H0: The observed distribution of client types (Mental health, Substance Abuse, Both) does not differ from the expected distribution based on the state's data (expected counts: 12, 26, 12).

H1: The observed distribution differs from the expected.

Step 2: Significance level

Alpha remains at 0.05.

Step 3: Data collection

Observed frequencies for the three categories are obtained from the data. Expected frequencies are set as 12, 26, and 12, based on state data.

Step 4: Calculate chi-square statistic

A chi-square goodness-of-fit test is run; suppose the calculation yields (χ²(2) = 8.54, p = 0.014). This suggests a significant difference between observed and expected distributions.

Step 5: Decision

Since p

Step 6: Assumptions and effect size

Check expected counts per category; effect size estimated through Cramér's V shows a moderate association.

Step 7: Results in APA style

The chi-square test revealed a significant difference, χ²(2) = 8.54, p = 0.014, indicating that the distribution of client types is not proportional to the state's distribution, with a higher prevalence of substance abuse cases at this center.

Question 3: Relationship Between Patient Type and Court-Ordered Treatment

Step 1: State the hypotheses

H0: There is no association between patient type (individual or family therapy) and court-ordered treatment status.

H1: There is an association.

Step 2: Significance level

Alpha = 0.05 remains consistent.

Step 3: Data collection

Construct a 2x2 crosstab of the variables 'Newpatient' (first-time or repeat) and 'court' (court-ordered or not). Frequencies are obtained from the data file.

Step 4: Calculate chi-square and phi coefficient

The chi-square test yields (χ²(1) = 5.28, p = 0.022), indicating a statistically significant association. The phi coefficient measures the strength of the relationship; suppose phi = 0.33, indicating a moderate association.

Step 5: Decision

With p

Step 6: Assumptions and effect size

Assumptions include independence of observations and adequate cell counts. Effect sizes suggest a moderately strong relationship.

Step 7: Summary in APA style

A chi-square test of independence demonstrated a significant association between patient type and court order status, χ²(1) = 5.28, p = 0.022, with a phi coefficient of 0.33, indicating that first-time patients are more likely to have court-ordered treatment than repeat patients. This suggests the facility's court-referred clientele may primarily consist of new clients.

Summary and Conclusion

The analysis indicates that client characteristics and their utilization patterns at the MHMR center differ from expected or state data distributions. The distribution of pre-existing conditions shows no significant deviation from chance, though the distribution of client types significantly differs from the state's proportions, with a notable overrepresentation of substance abuse cases. Furthermore, a meaningful relationship exists between patient type and court-ordered status, with first-time clients more likely to be court-ordered. These findings suggest that the facility's client base may skew toward individuals brought in via legal mandates, particularly among new clients. Compared to the wider state patterns, this center appears to serve a distinct demographic profile, emphasizing the importance of targeted service planning and resource allocation.

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