---
title: Hypothesis Testing Example - Teva Allergic Rhinitis Research - Calculate sample size
description: Hypothesis Testing Example - Use nQuery and learn how to calculate sample size and use a power analysis calculator for clinical trials. This example focuses on Teva Allergic Rhinitis Research.
image: https://www.statsols.com/hubfs/Master_Images/___HeroBannerImages/nQuery%20Sample%20Size%20Software%20Image.png
---

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## Sample Size Determination Example

# AREA: Means | Respiratory

![nQuery In Use Background Web  Opacity 35](https://www.statsols.com/hs-fs/hubfs/Master_Images/___HeroBannerImages/nQuery%20In%20Use%20Background%20Web%20%20Opacity%2035.png?width=1920&name=nQuery%20In%20Use%20Background%20Web%20%20Opacity%2035.png "nQuery In Use Background Web  Opacity 35")

#### Teva Allergic Rhinitis Research

#### Title: Safety and efficacy of once-daily treatment with beclomethasone dipropionate nasal aerosol in subjects with perennial allergic rhinitis

**Objective: **Intranasal corticosteroids are recommended as first-line therapy for the treatment of the symptoms of persistent allergic rhinitis (AR). Since the phase-out of chlorofluorocarbon nasal aerosols, intranasal corticosteroids have been available only as aqueous nasal sprays. This study was designed to assess the efficacy, safety, and quality-of-life benefits of beclomethasone dipropionate (BDP) hydrofluoroalkane nasal aerosol in subjects with perennial AR (PAR).

**Year:** 2012

**Source:** Allergy and Asthma Proceedings

**Link:<https://www.ingentaconnect.com/content/ocean/aap/2012/00000033/00000003/art00007%3bjsessionid=71tqtnde4n2nt.x-ic-live-01>**[https://www.ingentaconnect.com/content/ocean/aap/2012/00000033/00000003/art00007%3bjsessionid=71tqtnde4n2nt.x-ic-live-01](https://www.ingentaconnect.com/content/ocean/aap/2012/00000033/00000003/art00007%3bjsessionid=71tqtnde4n2nt.x-ic-live-01)

**Clinical Area: **Respiratory

| **Sample Size Section in Paper/Protocol:** |
| --- |
| “Using a standard deviation of 2.0, it was estimated that 235 subjects/treatment group would provide 90% power to detect a difference between the treatment groups of 0.6 in the change from baseline in average A.M. and P.M. subject-reported rTNSS with a two-sided α-level of 0.05.” |

**  
Summary of Necessary Parameter Estimates for Sample Size Calculation:**

|  Parameter | Value |
| --- | --- |
|  Significance Level (2-Sided) | 0.05 |
|  Difference | 0.35 |
|  Standard Deviation | 0.7 |
|  Power | 90% |

#### **Email me this example in PDF format**

**Step 1:  
**Select the **Two Sample Student’s T-test (equal variances)** table from the Select Test Design & Goal window.

This can be done **using the radio buttons** or alternatively, you can** use the search bar** at the end of the Select Test Design & Goal window.

![Sample Size Calculator Example- nQuery- Example 14- Img 01- Two Sample Student’s T-test (equal variances)](https://www.statsols.com/hs-fs/hubfs/Master_Images/___PageImages/Worked%20Examples/nQuery%20Example%20Images/Sample%20Size%20Calculator%20Example-%20nQuery-%20Example%2014-%20Img%2001-%20Two%20Sample%20Student%E2%80%99s%20T-test%20(equal%20variances).png?width=581&name=Sample%20Size%20Calculator%20Example-%20nQuery-%20Example%2014-%20Img%2001-%20Two%20Sample%20Student%E2%80%99s%20T-test%20(equal%20variances).png)

**Step 2:  
**Enter the values for sample size calculation taken from the study design statement and survival parameter converter.

![Sample Size Calculator Example- nQuery- Example 14- Img 02- Two Sample Student’s T-test (equal variances)](https://www.statsols.com/hs-fs/hubfs/Master_Images/___PageImages/Worked%20Examples/nQuery%20Example%20Images/Sample%20Size%20Calculator%20Example-%20nQuery-%20Example%2014-%20Img%2002-%20Two%20Sample%20Student%E2%80%99s%20T-test%20(equal%20variances).png?width=470&name=Sample%20Size%20Calculator%20Example-%20nQuery-%20Example%2014-%20Img%2002-%20Two%20Sample%20Student%E2%80%99s%20T-test%20(equal%20variances).png)

**Step 3:  
**Once the relevant Power is entered in the power row, the sample size is calculated automatically.

| This gives a sample size of 235, as per the study design |
| --- |

 

**![Sample Size Calculator Example- nQuery- Example 14- Img 03- Two Sample Student’s T-test (equal variances)](https://www.statsols.com/hs-fs/hubfs/Master_Images/___PageImages/Worked%20Examples/nQuery%20Example%20Images/Sample%20Size%20Calculator%20Example-%20nQuery-%20Example%2014-%20Img%2003-%20Two%20Sample%20Student%E2%80%99s%20T-test%20(equal%20variances).png?width=476&name=Sample%20Size%20Calculator%20Example-%20nQuery-%20Example%2014-%20Img%2003-%20Two%20Sample%20Student%E2%80%99s%20T-test%20(equal%20variances).png)**

*In the case of the ANCOVA analysis used in the study, the only additional information necessary would be an estimate of R2 between the response and the covariates. For example, using the ANCOVA sample size table available in nQuery Advanced for the above study and assuming a 10% R2 between baseline and the response would have yielded an adjusted sample size of 211 per group.*

**Step 4:  
**Once the calculation is completed, nQuery Advanced provides an output statement summarizing the results. It States:

| **Output Statement:** |
| --- |
| *A sample size of 235 in each group will have 90% power to detect a difference in means of 0.6 assuming that the common standard deviation is 2 using a two group t-test with a 5% two-sided significance level.* |

 

![Sample Size Calculator Example- nQuery- Example 14- Img 04- Two Sample Student’s T-test (equal variances)](https://www.statsols.com/hs-fs/hubfs/Master_Images/___PageImages/Worked%20Examples/nQuery%20Example%20Images/Sample%20Size%20Calculator%20Example-%20nQuery-%20Example%2014-%20Img%2004-%20Two%20Sample%20Student%E2%80%99s%20T-test%20(equal%20variances).png?width=641&name=Sample%20Size%20Calculator%20Example-%20nQuery-%20Example%2014-%20Img%2004-%20Two%20Sample%20Student%E2%80%99s%20T-test%20(equal%20variances).png)

#### **Email me this example in PDF format**

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